Books by Subject

Computational Biology

  • Digital
    James M. Bower, editor.
    Springer2013
  • Digital
    Jesse M. Rodriguez.
    The predisposition to many diseases is strongly influenced by the genome of an individual. However, the association between the genome and most diseases is not fully understood, so there is an ongoing effort to characterize these associations. One way to characterize disease-genome associations is by studying the familial and ancestral origin of individuals in the context of disease. This kind of study relies on the fact that individuals with shared origins tend to have genomes and phenotypes that are similar to one another. Detailed information regarding familial and ancestral origin is often unknown, however, it can be inferred computationally by examining the genome. Therefore, it is important that we have accurate methods to infer this information in order to facilitate disease-genome associations. In this dissertation, I describe the contributions I have made to accurately inferring the ancestry and relatedness of individuals based on their genomes. First, I describe my work on ALLOY, a method to infer the ancestral origin of segments of the genome based on a factorial HMM. Next, I present PARENTE, a method to infer which individuals in a group are related to one another by detecting genomic segments that are identical-by-descent (IBD) using an embedded likelihood ratio test. Finally, I present PARENTE2, an extension of PARENTE that incorporates linkage disequilibrium information and results in significantly higher accuracy.
  • Digital/Print
    Dongqing Wei, Qin Xu, Tangzhen Zhao, Hao Dai, editors.
    Digital : Springer2015
    Print2015
    This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As such, it emphasizes programming and problem-solving skills. It provides information on structure bioinformatics at various levels, with individual chapters covering introductory to advanced aspects, from fundamental methods and guidelines on acquiring and analyzing genomics and proteomics sequences, the structures of protein, DNA and RNA, to the basics of physical simulations and methods for conformation searches. This book will be of immense value to researchers and students in the fields of bioinformatics, computational biology and chemistry. Dr. Dongqing Wei is a Professor at the Department of Bioinformatics and Biostatistics, College of Life Science and Biotechnology, Shanghai Jiaotong University, Shanghai, China. His research interest is in the general area of structural bioinformatics.
  • Digital/Print
    Hamid R. Arabnia, editor.
    Digital : Springer2010
    Print2010
    Bioinformatics databases, data mining, and pattern discovery -- Microarray, gene expression analysis, and gene regulatory networks -- Protein classification & structure prediction, and computational structural biology -- Comparative sequence, genome analysis, genome assembly, and genome scale computational methods -- Drug design, drug screening, and related topics -- Computational methods and diagnostic tools in biomedical -- General topics in bioinformatics.
  • Digital
    volume editors, Anatoliy I. Yashin, Durham, NC, Michal Jazwinsk, New Orleans, La.
    Karger2015
    Introduction to the theory of aging networks / Witten, T.M. -- Applications to aging networks / Wimble, C., Witten, T.M. -- Computational systems biology for aging research / Auley, M.T., Mooney, K.M. -- How does the body know how old it is? Introducing the epigenetic clock hypothesis / Mitteldorf, J. -- The great evolutionary divide : two genomic systems biologies of aging / Rose, M.R., Cabral, I.G., Philips, M.A., Rutledge, G.A., Phung, K.H., Mueller, L.D., Greer, L.F. -- Development and aging : two opposite but complementary phenomena / Feltes, B.C., De Faria Poloni, J., Bonatto, D. -- Aging as a process of deficit accumulation : its utility and origin / Mitnitski, A., Rockwood, K. -- Low-grade systemic inflammation connects aging, metabolic syndrome and cardiovascular disease / Guarner, V., Rubio-Ruiz, M.E. -- Modulating mTOR in aging and health / Johnson, S.C., Sangesland, M., Kaeberlein, M., Rabinovitch, P. -- Melatonin and circadian oscillators in aging : a dynamic approach to the multiply connected players / Hardeland, R. -- Diet-microbiota-health interactions in older subjects : implications for healthy aging / Lynch, D.B., Jeffery, I.B., Cusack, S., O'Connor, E.M., O'Toole, P.W. -- Systems biology approaches in aging research / Chauhan, A., Liebal, U.W., Vera, J., Baltrusch, S., Junghanss, C., Tiedge, M., Fuellen, G., Wolkenhauer, O., Köhling, R. -- Conservative growth hormone/IGF-1 and mTOR signaling pathways as a target for aging and cancer prevention : do we really have an antiaging drug? / Anisimov, V.N.
  • Digital
    Eugene Davydov.
    Availability of massive amounts of genomic data from hundreds of species has introduced many challenging computational problems as well as the need for efficient algorithmic tools that leverage multiple species information to facilitate biological analysis. This dissertation discusses two such problems: noncoding RNA multiple structural alignment and constrained element detection. Noncoding RNA genes (ncRNAs) are regions of the genome that are transcribed but not translated into protein, and fold directly into secondary and tertiary structures which can have a variety of important biological functions. Because their function depends closely on the secondary structure, ncRNAs often do not exhibit enough primary sequence conservation to be properly aligned using standard sequence-based methods. I therefore consider the problem of RNA multiple structural alignment, i.e., performing sequence alignment and secondary structure prediction simultaneously. In the first part of this dissertation I introduce a novel graph theoretic framework for analyzing this problem and prove that when the number of sequences is not fixed it is NP-complete. I also provide a polynomial time algorithm that approximates the optimal solution to within a factor of O(log^2 n). Constrained elements are regions of the human genome exhibiting evidence of purifying selection and therefore biological function. Computational identification of such elements is one of the major goals of comparative genomics. In the second part of this dissertation I present GERP++, a new tool for efficient constrained element detection that significantly improves on one of the current leading methods, GERP. While retaining GERP's biological transparency and metric for quantifying position-specific constraint, GERP++ uses a more rigorous method for computing evolutionary rates and a novel algorithm for element identification that uses statistical significance directly to evaluate and rank candidate elements. These algorithmic improvements decrease the running time by several orders of magnitude in practice, enabling high-throughput analysis of large data sets. Furthermore, I present analysis and biological interpretation of constrained elements identified by GERP++ in the human genome from recently available multiple species alignments.
  • Digital
    Ailin Tao, Eyal Rax, editors.
    Springer2015
    Allergic Disease Epidemiology -- The Pathogenesis of Allergy: A Brief Introduction -- Genetics and Epigenetic Regulation in Allergic Diseases -- Cross-Reactivity -- From Allergen Extracts to Allergen Genes and Allergen Molecules -- Allergen Gene Cloning -- High Throughput Screening of Allergy -- Surrogate Markers for Allergen-Specific Immunotherapy -- Immune Responses to Allergens in Atopic Disease: Considerations for Bioinformatics -- Antigenicity, Immunogenicity and Allergenicity -- Bioinformatic Classifiers for Allergen Sequence Discrimination -- Strategies for the Modification and Evaluation of Allergenicity -- Bioinformatics Methods to Predict Allergen Epitopes -- Allergen Database.
  • Digital
    edited by Eleftheria Zeggini, Andrew Morris.
    ScienceDirect2011
    According to the National Institute of Health, a genome-wide association study is defined as any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition. Whole genome information, when combined with clinical and other phenotype data, offers the potential for increased understanding of basic biological processes affecting human health, improvement in the prediction of disease and patient care, and ultimately the realization of the promise of personalized medicine. In addition, rapid advances in understanding the patterns of human genetic variation and maturing high-throughput, cost-effective methods for genotyping are providing powerful research tools for identifying genetic variants that contribute to health and disease. This burgeoning science merges the principles of statistics and genetics studies to make sense of the vast amounts of information available with the mapping of genomes. In order to make the most of the information available, statistical tools must be tailored and translated for the analytical issues which are original to large-scale association studies. This book will provide researchers with advanced biological knowledge who are entering the field of genome-wide association studies with the groundwork to apply statistical analysis tools appropriately and effectively. With the use of consistent examples throughout the work, chapters will provide readers with best practice for getting started (design), analyzing, and interpreting data according to their research interests. Frequently used tests will be highlighted and a critical analysis of the advantages and disadvantage complimented by case studies for each will provide readers with the information they need to make the right choice for their research.
  • Digital
    edited by Nataa Prulj, University College London.
    Cambridge2019
    The increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straightforward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network data analysis in biomedicine.
  • Digital
    Shizuka Uchida.
    ScienceDirect2012
    In recent years, the advent of high-throughput analytical techniques, such as microarrays and serial analysis of gene expression, has led to a rapid accumulation of biological data. To cope with these new challenges and to facilitate efficient data analyses, numerous academic and commercial databases have been developed.
  • Digital
    edited by Xiangdong Wang, Christian Baumgartner, Denis C. Shields, Hong-Wen Deng, Jacques S Beckmann.
    Springer2016
    The Era of Big Data: From Data-driven Research to Data-driven Clinical Care -- Biostatistics, data mining and computational modeling -- Gene expression and profiling -- The next generation sequencing and applications in clinical research -- Clinical epigenetics and epigenomics -- Proteomic profiling: Data mining and analyses -- Targeted metabolomics: the next generation of clinical chemistry!? -- Clinical bioinformatics for biomarker discovery in targeted metabolomics -- Metagenomic Profiling, Interaction of Genomics with Meta-genomics -- Clinical Epigenetics and Epigenomics -- Integrative Biological Databases -- Standards and Regulations for (Bio)Medical Software -- Clinical applications and systems biomedicine -- Key Law and Policy Considerations for Clinical Bioinformaticians -- Challenges and Opportunities in Clinical Bioinformatics -- Heterogeneity of Hepatocellular Carcinoma.
  • Digital
    P.M. Selzer, R.J. Marhöfer, A. Rohwer ; [translators, P.D. Frank Seeber, Conor Caffrey].
    Springer2008
  • Digital
    editor, Yin Yao Shugart.
    Springer2012
    Applied Computational Genomics' focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics.
  • Digital
    Peter J. Bentley, Doheon Lee, Sungwon Jung (eds.).
    Springer2008
  • Digital
    Ms Rong Xu.
    Advances in medical research, pharmaceuticals, treatment options, and biotechnology are occurring at an explosive rate. As of 2009, there are 19 million of biomedical research abstracts available on MEDLINE and 1.3 billion searches of MEDLINE are done in 2009. Most of the popular search engines, from Google to PubMed, use keyword-based information retrieval methods, often overloading users with irrelevant information. At the same time, keyword-based search engines cannot answer simple biomedical questions, such as "what are the breast cancer treatment drugs" or "what are the breast cancer associated genes". Answering such questions requires machine understandable knowledge to be extracted from free text. My thesis represents an automated system to extract machine understandable biomedical information from MEDLINE abstracts using machine learning and natural language processing ( NLP ) techniques. The system is different from current biomedical information extraction systems in the following: 1. the system is semi-supervised where the only human supervision is a single pattern for each information type; 2. it can be used to extract broad types of information, including named entities and relationships among entities.
  • Digital
    edited by Alessio Mengoni, Marco Galardini, Marco Fondi.
    Springer2015
    Pulsed field gel electrophoresis and genome size estimates/ Rosa Alduina and Annalisa Pisciotta -- Comparative analyses of extrachromosomal bacterial replicons, identification of chromids, and experimental evaluation of their indispensability / Lukasz Dziewit and Dariusz Bartosik -- Choice of next-generation sequencing pipelines / F. Del Chierico ... [et al.] -- Pyrosequencing protocol for bacterial genomes / Ermanno Rizzi -- Bacterial metabarcoding by 16S rRNA gene ion torrent amplicon sequencing / Elio Fantini ... [et al.] -- Illumina-solexa sequencing protocol for bacterial genomes / Zhenfei Hu, Lei Cheng, and Hai Wang -- High-throughput phenomics / Carlo Viti ... [et al.] -- Comparative analysis of gene expression : uncovering expression conservation and divergence between Salmonella enterica serovar typhimurium strains LT2 and 14028S / Paolo Sonego ... [et al.] -- Raw sequence data and quality control / Giovanni Bacci -- Methods for assembling reads and producing contigs / Valerio Orlandini, Marco Fondi, and Renato Fani -- Mapping contigs using CONTIGuator / Marco Galardini, Alessio Mengoni, and Marco Bazzicalupo -- Gene calling and bacterial genome annotation with BG7 / Raquel Tobes ... [et al.] -- Defining orthologs and pangenome size metrics / Emanuele Bosi, Renato Fani, and Marco Fondi -- Robust identification of orthologues and paralogues for microbial pan-genomics using GET HOMOLOGUES : a case study of pIncA/C plasmids / Pablo Vinuesa and Bruno Contreras-Moreira -- Genome-scale metabolic network reconstruction / Marco Fondi and Pietro Liò -- From pangenome to panphenome and back / Marco Galardini, Alessio Mengoni, and Stefano Mocali -- Genome-wide detection of selection and other evolutionary forces / Zhuofei Xu and Rui Zhou -- Integrated microbial genome resource of analysis / Alice Checcucci and Alessio Mengoni.
  • Digital/Print
    Marco Fioroni, Tamara Dworeck, Francisco Rodriguez-Ropero.
    Digital : Springer2014
    Print2014
    β-barrel outer membrane channel proteins (OMP) have great potential as robust and flexible models or components in nanotechnology. Over the last decade biotechnological techniques allowed to expand the natural characteristics of OMPs by modifying their geometry and properties without affecting the overall protein structure and stability. The present book is oriented towards a broad group of readers including graduate students and advanced researchers. The β-barrel structure serviceability for the nano-material design will be its chief topic giving a general introduction to the field of OMP based nano-component development as well as the state of the art of the involved research. On the example of the E. coli FhuA the transformation of an OMP into a tailored nano-channel to be adapted to a non-biological synthetic (i.e. polymer) environment, rendering it competitive with artificial non-biological nano-pores will be outlined specifically the design of a set of protein nano-channels with tailored geometry (diameter, length), conductance and functionality will be reported as a case study. In order to make this book a valuable source of information for both biotechnologists and other scientists interested in bio-nanotechnology an overview of the different steps involved in the nano-channel protein design and production will be reported. The scientific strategy from concept design, theoretical considerations, genetic engineering and large scale production, to system assembly and biophysical characterization with an overview on technological applications including membrane/polymersome technology, will be described.
  • Digital
    Pouria Amirian, Trudie Lang, Francois van Loggerenberg, editors.
    Springer2017
    This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data? What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices? This book shows how it is feasible to store vast numbers of anonymous data and ask highly specific questions that can be performed in real-time to give precise and meaningful evidence to guide public health policy.
  • Digital
    edited by Jonathan M. Keith.
    Springerv. 1, 2008
    Springerv. 2, 2008
    v. 1. Data, sequence analysis, and evolution -- v. 2. Structure, function, and applications.
  • Digital
    Venkatarajan Subramanian Mathura and Pandjassarame Kangueane, [editors].
    Springer2009
  • Digital
    edited by M.H. Fulekar.
    Springer2009
  • Digital
    David Edwards, Jason E. Stajich, David Hansen, editors.
    Springer2009
    DNA Sequence Databases / David Edwards, David Hansen and Jason E. Stajich -- Sequence Comparison Tools / Michael Imelfort -- Genome Browsers / Sheldon McKay and Scott Cain -- Predicting Non-coding RNA Transcripts / Laura A. Kavanaugh and Uwe Ohler -- Gene Prediction Methods / William H. Majoros, Ian Korf and Uwe Ohler -- Gene Annotation Methods / Laurens Wilming and Jennifer Harrow -- Regulatory Motif Analysis / Alan Moses and Saurabh Sinha -- Molecular Marker Discovery and Genetic Map Visualisation / Chris Duran, David Edwards and Jacqueline Batley -- Sequence Based Gene Expression Analysis / Lakshmi K. Matukumalli and Steven G. Schroeder -- Protein Sequence Databases / Terry Clark -- Protein Structure Prediction / Sitao Wu and Yang Zhang -- Classification of Information About Proteins / Amandeep S. Sidhu, Matthew I. Bellgard and Tharam S. Dillon -- High-Throughput Plant Phenotyping - Data Acquisition, Transformation, and Analysis / Matthias Eberius and José Lima-Guerra -- Phenome Analysis of Microorganisms / Christopher M. Gowen and Stephen S. Fong -- Standards for Functional Genomics / Stephen A. Chervitz, Helen Parkinson, Jennifer M. Fostel, Helen C. Causton and Susanna-Assunta Sanson, et al. -- Literature Databases / J. Lynn Fink -- Advanced Literature-Mining Tools / Pierre Zweigenbaum and Dina Demner-Fushman -- Data and Databases / Daniel Damian -- Programming Languages / John Boyle.
  • Digital
    edited by Jonathan M. Keith.
    Springer2017
    This second edition provides updated and expanded chapters covering a broad sampling of useful and current methods in the rapidly developing and expanding field of bioinformatics. Bioinformatics, Volume I: Data, Sequence Analysis, and Evolution, Second Edition is comprised of three sections: Data and Databases, Sequence Analysis, and Phylogenetics and Evolution. The first section details bioinformatics methodologies in the generation of sequence and structural data and its organization into conceptual categories, and databases to facilitate further analyses. The Sequence Analysis section describes the fundamental methodologies for processing the sequences of biological molecules: techniques that are used in almost every pipeline of bioinformatics analysis, particularly in the preliminary stages of such pipelines. Last but not least, the phylogenetics and evolution section deals with methodologies that compare biological sequences for the purpose of understanding how they evolved. As a volume in the highly successful Methods in Molecular Biology series, chapters feature the kind of detail and expert implementation advice to ensure positive results. Comprehensive and practical, Bioinformatics, Volume I: Data, Sequence Analysis, and Evolution, Second Edition is an essential resource for graduate students, early career researchers, and others who are in the process of integrating new bioinformatics methods into their research.
  • Digital
    edited by Jonathan M. Keith.
    Springer2017
    3D computational modeling of proteins using sparse paramagnetic NMR data / Kala Bharath Pilla, Gottfried Otting, and Thomas Huber -- Inferring function from homology / Tom C. Giles and Richard D. Emes -- Inferring functional relationships from conservation of gene order / Gabriel Moreno-Hagelsieb -- Structural and functional annotation of long noncoding RNAs / Martin A. Smith and John S. Mattick -- Construction of functional gene networks using phylogenetic profiles / Junha Shin and Insuk Lee -- Inferring genome-wide interaction networks / Gokmen Altay and Onur Mendi -- Integrating heterogeneous datasets for cancer nodule identification / A.K.M. Azad -- Metabolic pathway mining / Jan M. Czarnecki and Adrian J. Shepherd -- Analysis of genome-wide association data / Allan F. McRae -- Adjusting for familial relatedness in the analysis of GWAS data / Russell Thomson and Rebekah McWhirter -- Analysis of quantitative trait loci / David L. Duffy -- High-dimensional profiling for computational diagnosis / Claudio Lottaz, Wolfram Gronwald, Rainer Spang, and Julia C. Engelmann -- Molecular similarity concepts for informatics applications / Jssurgen Bajorath -- Compound data mining for drug discovery / Jssurgen Bajorath -- Studying antibody repertoires with next-generation sequencing / William D. Lees and Adrian J. Shepherd -- Using the QAPgrid visualization approach for biomarker identification of cell-specific transcriptomic signatures / Chloe Warren, Mario Inostroza-Ponta, and Pablo Moscato -- Computer-aided breast cancer diagnosis with optimal feature sets : reduction rules and optimization techniques / Luke Mathieson, Alexandre Mendes, John Marsden, Jeffrey Pond, and Pablo Moscato -- Inference method for developing mathematical models of cell signaling pathways using proteomic datasets / Tianhai Tian and Jiangning Song -- Clustering / G.J. McLachlan, R.W. Bean, and S.K. Ng -- Parameterized algorithmics for finding exact solutions of NP-hard biological problems / Falk Hssuffner, Christian Komusiewicz, Rolf Niedermeier, and Sebastian Wernicke -- Information visualization for biological data / Tobias Czauderna and Falk Schreiber.
  • Digital
    edited by William T. Loging.
    Cambridge2016
    "Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline"--Provided by publisher.
  • Digital
    edited by Richard S. Larson, the University of New Mexio, Albuqerque, NM, USA.
    Springer2012
    Cell perturbation screens for target identification by RNAi / Kubilay Demir and Michael Boutros -- Using functional genomics to identify drug targets : a Dupuytren's disease example / Mirela Sedic, Sandra Kraljevic Pavelic, and Karlo Hock -- Functional characterization of human genes from exon expression and RNA interference results / Dorothea Emig [and others] -- Barcode sequencing for understanding drug-gene interactions / Andrew M. Smith [and others] -- High-throughput sequencing of the methylome using two-base encoding / Christina A. Bormann Chung -- Applications and limitations of in silico models in drug discovery / Ahmet Sacan, Sean Ekins, and Sandhya Kortagere -- Compound Collection Preparation for Virtual screening / Cristian G. Bologa and Tudor I. Oprea -- Mapping between databases of compounds and protein targets / Sorel Muresan, Markus Sitzmann, and Christopher Southan -- Predictive cheminformatics in drug discovery : statistical modeling for analysis of micro-array and gene expression data / N. Sukumar, Michael P. Krein, and Mark J. Embrechts -- Advances in nuclear magnetic resonance for drug discovery / Laurel O. Sillerud and Richard S. Larson -- Human ABC transporter ABCG2 in cancer chemotherapy : drug molecular design to circumvent multidrug resistance / Toshihisa Ishikawa [and others] -- Protein interactions : mapping interactome networks to support drug target discovery and selection / Javier De Las Rivas and Carlos Prieto -- Linking variants from genome-wide association analysis to function via transcriptional network analysis / Benjamin J. Keller, Sebastian Martini, and Viji Nair -- Models of excitation-contraction coupling in cardiac ventricular myocytes / M. Saleet Jafri -- Integration of multiple ubiquitin signals in proteasome regulation / Marta Isasa, Alice Zuin, and Bernat Crosas.
  • Digital
    Frederick Marcus.
    Springer2008
  • Digital
    Kevin Byron, New Jersey Institute of Technology, Newark, USA, Katherine G. Herbert, Montclair State University, New Jersey, USA, Jason T.L. Wang, New Jersey Institute of Technolog, Newark, USA.
    TandFonline2017
    Chapter 1. Overview of bioinformatics databases -- Chapter 2. Biological data cleaning -- Chapter 3. Biological data integration -- Chapter 4. Biological data searching -- Chapter 5. Biological data mining -- Chapter 6. Biological network inference -- Chapter 7. Cloud-based biological data processing.
  • Digital
    Kung-Hao Liang.
    ScienceDirect2013
    1. Introduction -- 2. Genomics -- 3. Transcriptomics -- 4. Proteomics -- 5. Systems biomedical science -- 6. Clinical developments -- 7. Conclusions.
  • Digital
    edited by Cathy H. Wu, Chuming Chen.
    Springer2011
    Protein bioinformatics databases and resources -- A guide to UniProt for protein scientists -- Interpro protein classification -- Reactome knowledgebase of human biological pathways and processes -- eFIP: A tool for mining functional impact of phosphorylation from literature -- A tutorial on protein ontology resources for proteomic studies -- Structure-guided rule-based annotation of protein functional sites in UniProt knowledgebase -- Modeling mass spectrometry-based protein analysis -- Protein identification from tandem mass spectra by database searching -- LC-MS data analysis for differential protein expression detection -- Protein identification by spectral networks analysis -- Software pipeline and data analysis for ms/ms proteomics: The trans-proteomic pipeline -- Analysis of high-throughput ELISA microarray data -- Proteomics databases and repositories -- Preparing molecular interaction data for publication -- Submitting proteomics data to PRIDE using PRIDE converter -- Automated data integration and determination of posttranslational modifications with the protein inference engine -- An integrated top-down and bottom-up strategy for characterization of protein isoforms and modifications -- Phosphoproteome resource for systems biology research -- Protein-centric data integration for functional analysis of comparative proteomics data -- Integration of proteomic and metabolomic profiling as well as metabolic modeling for the functional analysis of metabolic networks -- Time series proteome profiling.
  • Digital
    editor: Bairong Shen.
    Springer2013
    The book introduces the bioinformatics tools, databases and strategies for the translational research, focuses on the biomarker discovery based on integrative data analysis and systems biological network reconstruction. With the coming of personal genomics era, the biomedical data will be accumulated fast and then it will become reality for the personalized and accurate diagnosis, prognosis and treatment of complex diseases. The book covers both state of the art of bioinformatics methodologies and the examples for the identification of simple or network biomarkers. In addition, bioinformatics software tools and scripts are provided to the practical application in the study of complex diseases. The present state, the future challenges and perspectives were discussed. The book is written for biologists, biomedical informatics scientists and clinicians, etc.
  • Digital
    edited by David Posada.
    Springer2009
    Similarity searching using BLAST / Kit J. Menlove, Mark Clement, and Keith A. Crandall -- Gene orthology assessment with OrthologID / Mary Egan ... [et al.] -- Multiple alignment of DNA sequences with MAFFT / Kazutaka Katoh, George Asimenos, and Hiroyuki Toh -- SeqVis : a tool for detecting compositional heterogeneity among aligned nucleotide sequences / Lars Sommer Jermiin ... [et al.] -- Selection of models of DNA evolution with jModelTest / David Posada -- Estimating maximum likelihood phylogenies with PhyML / Stéphane Guindon ... [et al.] -- Trees from trees : construction of phylogenetic supertrees using clann / Christopher J. Creevey and James O. McInerney -- Detecting signatures of selection from DNA sequences using datamonkey / Art F.Y. Poon, Simon D.W. Frost, and Sergei L. Kosakovsky Pond -- Recombination detection and analysis using RDP3 / Darren P. Martin -- CodonExplorer : an interactive online database for the analysis of codon usage and sequence composition / Jesse Zaneveld ... [et al.] -- Genetic code prediction for metazoan mitochondria with GenDecoder / Federico Abascal, Rafael Zardoya, and David Posada -- Computational gene annotation in new genome assemblies using GeneID / Enrique Blanco and Josep F. Abril -- Promoter analysis : gene regulatory motif identification with A-GLAM / Leonardo Mariño-Ramírez ... [et al.] -- Analysis of genomic DNA with the UCSC Genome Browser / Jonathan Pevsner -- Mining for SNPs and SSRs using SNPServer, dbSNP and SSR taxonomy tree / Jacqueline Batley and David Edwards -- Analysis of transposable element sequences using CENSOR and RepeatMasker / Ahsan Huda and I. King Jordan -- DNA sequence polymorphism analysis using DnaSP / Julio Rozas.
  • Digital
    Naiara Rodríguez-Ezpeleta, Michael Hackenberg, Ana M. Aransay, editors.
    Springer2012
    Overview of sequencing technology platforms / Samuel Myllykangas, Jason Buenrostro, and Hanlee P. Ji -- Applications of high-throughput sequencing / Rodrigo Goya, Irmtraud M. Meyer, and Marco A. Marra -- Computational infrastructure and basic data analysis for high-throughput sequencing / David Sexton -- Base-calling for bioinformaticians / Mona A. Sheikh and Yaniv Erlich -- De novo short-read assembly / Douglas W. Bryant Jr. and Todd C. Mockler -- Short-read mapping / Paolo Ribeca -- DNA-protein interaction analysis (ChIP-Seq) / Geetu Tuteja -- Generation and analysis of genome-wide DNA methylation maps / Martin Kerick, Axel Fischer, and Michal-Ruth Schweiger -- Differential expression for RNA sequencing (RNA-Seq) data : mapping, summarization, statistical analysis, and experimental design / Matthew D. Young ... [et al.] -- MicroRNA expression profiling and discovery / Michael Hackenberg -- Dissecting splicing regulatory network by integrative analysis of CLIP-Seq data / Michael Q. Zhang -- Analysis of metagenomics data / Elizabeth M. Glass and Folker Meyer -- High-throughput sequencing data analysis software : current state and future developments / Konrad Paszkiewicz and David J. Studholme.
  • Digital
    Darren R. Flower, Matthew N. Davies, Shoba Ranganathan, editors.
    Springer2010
  • Digital
    edited by Bernd Mayer.
    Springer2011
    [Publisher-supplied data] Presenting an area of research that intersects with and integrates diverse disciplines, including molecular biology, applied informatics, and statistics, among others, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study. Divided into three convenient sections, this detailed volume covers central analysis strategies, standardization and data-management guidelines, and fundamental statistics for analyzing Omics profiles, followed by a section on bioinformatics approaches for specific Omics tracks, spanning genome, transcriptome, proteome, and metabolome levels, as well as an assortment of examples of integrated Omics bioinformatics applications, complemented by case studies on biomarker and target identification in the context of human disease. Written in the highly successful Methods in Molecular Biology series format, chapters contain introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and accessible, Bioinformatics for Omics Data: Methods and Protocols serves as an ideal guide to scientists of all backgrounds and aims to convey the appropriate sense of fascination associated with this research field.
  • Digital
    edited by Gavin J. Gordon.
    Springer2009
    The emergence of bioinformatics : historical perspective, quick overview and future trends / Christos A. Ouzounis -- The statistical design and interpretation of microarray experiments / Kevin K. Dobbin and Richard M. Simon -- Whole-genome analysis of cancer / Steven A. Enkemann ... [et al.] -- Bioinformatics approaches to the analysis of the transcriptome of animal models of cancer / Mark J. Hoenerhoff ... [et al.] -- Significance of aberrant expression of miRNAs in cancer cells / George A. Calin ... [et al.] -- Proteomic methods in cancer research / Scot Weinberger and Egisto Boschetti -- Comprehensive genomic profiling for biomarker discovery for cancer detection, diagnostics and prognostics / Xiaofeng Zhou ... [et al.] -- Gene expression profiling of the leukemias : oncogenesis, drug responsiveness, and prediction of clinical outcome / Lars Bullinger, Hartmut Dohner, and Jonathon R. Pollack -- Personalized medicine in the clinical management of colorectal cancer / Anthony El-Khoueiry and Heinz Josef Lenz -- PIK3CA gene alterations in human cancers / Sérgia Velho, Carla Oliveira, and Raquel Seruca.
  • Digital
    editors Jingshan Huang, Glen M. Borchert, Dejing Dou, Jun (Luke) Huan, Wenjun Lan, Ming Tan, Bin Wu.
    Springer2017
    This thorough volume provides an in-depth introduction to and discussion of microRNAs (miRs) and their targets, miR functions, and computational techniques applied in miR research, thus serving the need for a comprehensive book focusing on miR target genes, miR regulation mechanisms, miR functions performed in various human diseases, and miR databases/knowledgebases. Without prior knowledge of the area of study, computational biologists, computer scientists, bioinformaticians, bench biologists, as well as clinical investigators will find it easy to follow the techniques in this collection. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that ensures successful results. Accessible and practical, Bioinformatics in MicroRNA Research functions as an ideal guide for researchers of all backgrounds to explore this vital area of study.
  • Digital
    editors, Arthur Gruber, Alan M. Durham, Chuong Huynh, and Hernado A. del Portillo.
    NCBI Bookshelf2008
    "This book is intended to serve both as a textbook for short bioinformatics courses and as a base for a self-teaching endeavor. "--Introduction.
  • Print
    Jorge L. Contreras and A. James Cuticchia, editors.
    "The book begins with an overview of the evolving bioinformatics field then explores legal issues surrounding the software tools that enable large-scale computational biology, including procurement and licensing of commercial software systems, in-house and contracted software development and issues surrounding open source software. Legal issues associated with software tools for large-scale computational biology are examined, including procurement and licensing of commercial software systems, in-house and contracted software development, and open source software." -- [Publisher-supplied data]
  • Digital
    editor: Xiangdong Wang.
    Springer2013
    Clinical Bioinformatics in Human Proteomics Research / Duojiao Wu, Haihao Li -- Proteomics Defines Protein Interaction Network of Signaling Pathways / Shitao Li -- Protein Function Microarrays: Design, Use and Bioinformatic Analysis in Cancer Biomarker Discovery and Quantitation / Jessica Duarte, Jean-Michel Serufuri, Nicola Mulder -- Proteomics and Cancer Research / Elena Lopez Villar -- Toward Development of Novel Peptide-Based Cancer Therapeutics: Computational Design and Experimental Evaluation / Elena Pirogova, Taghrid Istivan -- Advances in Proteomic Methods / Xianyin Lai -- Clinical and Biomedical Mass Spectrometry: New Frontiers in Drug Developments and Diagnosis / Ákos Végvári, Melinda Rezeli -- Disease Biomarkers: Modelling MR Spectroscopy and Clinical Applications / Luis Martí-Bonmati -- Processing of Mass Spectrometry Data in Clinical Applications / Dario Di Silvestre, Pietro Brunetti, Pier Luigi Mauri -- Bioinformatics Approach for Finding Target Protein in Infectious Disease / Hemant Ritturaj Kushwaha, Indira Ghosh -- Identification of Network Biomarkers for Cancer Diagnosis / Jiajia Chen, Luonan Chen -- Software Development for Quantitative Proteomics Using Stable Isotope Labeling / Xin Huang, Shi-Jian Ding -- Clinical Translation of Protein Biomarkers Integrated with Bioinformatics / Xu Yang, Juanjuan Zhou, Chaoqin Du -- Proteomic Approaches for Urine Biomarker Discovery in Bladder Cancer / Ming-Hui Yang, Yu-Chang Tyan -- Antibody Microarrays and Multiplexing / Jerry Zhou, Larissa Belov, Nicola Armstrong -- Proteomics in Anaesthesia and Intensive Care Medicine / Ornella Piazza, Giuseppe De Benedictis.
  • Digital
    Ion Măndoiu, Raj Sunderraman, Alexander Zelikovsky (eds.).
    Springer2008
  • Digital
    Pandjassarame Kangueane.
    Springer2009
  • Digital
    edited by Tatiana V. Tatarinova, Yuri Nikolsky.
    Springer2017
    In this volume, expert practitioners present a compilation of methods of functional data analysis (often referred to as “systems biology”) and its applications in drug discovery, medicine, and basic disease research. It covers such important issues as the elucidation of protein, compound and gene interactions, as well as analytical tools, including networks, interactome and ontologies, and clinical applications of functional analysis. As a volume in the highly successful Methods in Molecular Biology series, this work provides detailed description and hands-on implementation advice. Reputable, comprehensive, and cutting-edge, Biological Networks and Pathway Analysis presents both “wet lab” experimental methods and computational tools in order to cover a broad spectrum of issues in this fascinating new field.
  • Digital/Print
    Edward H. Shortliffe, editor; James J. Cimino, associate editor.
    Digital : Springer2006
    Print2006
  • Digital
    Cimino, James J.; Shortliffe, Edward H.
    Springer2014
    Biomedical Informatics: Computer Applications in Health Care and Biomedicine meets the growing demand of practitioners, researchers, educators, and students for a comprehensive introduction to key topics in the field and the underlying scientific issues that sit at the intersection of biomedical science, patient care, public health, and information technology (IT). This 4th edition reflects the remarkable changes in both computing and health care that continue to occur and the exploding interest in the role that IT must play in care coordination and the melding of genomics with innovations in clinical practice and treatment. New chapters have been introduced on the health information infrastructure, consumer health informatics, telemedicine, translational bioinformatics, clinical research informatics, and health IT policy, while the others have all undergone extensive revisions, in many cases with new authors. The organization and philosophy are unchanged, focusing on the science of information and knowledge management and the role of computers and communications in modern biomedical research, health, and health care. Emphasizing the conceptual basis of the field rather than technical details, it provides an introduction and extensive bibliography so that readers can comprehend, assess, and utilize biomedical informatics and health IT. The volume focuses on easy-to-understand examples, a guide to additional literature, chapter summaries, and a comprehensive glossary with concise definitions of recurring terms for self-study or classroom use.
  • Digital
    Michael F. Ochs, John T. Casagrande, Ramana V. Davuluri, editors.
    Springer2010
  • Digital/Print
    edited by Slobodan Vukicevic, Kuber T. Sampath.
    Digital : Springer2017
    Print2017
    Historical perspective of bone morphogenetic proteins -- The systems biology of bone morphogenetic proteins -- Embryonic skeletogenesis and craniofacial development -- BMP and BMP regulation: structure and function -- Novel in vitro assay models to study osteogenesis and chondrogenesis for human skeletal disorders -- Toward advanced therapy medicinal products (ATMPs) combining bone morphogenetic proteins (BMP) and cells for bone regeneration -- BMP signaling in articular cartilage repair and regeneration: potential therapeutic opportunity for osteoarthritis -- BMPs in orthopaedic medicine: promises and challenges -- Osteogrow: a novel graft substitute for orthopedic reconstruction -- Biology of spine fusion and application of osteobiologics in spine surgery -- BMPs in dental medicine: promises and challenges -- Bone morphogenetic protein-7 and its role in acute kidney injury and chronic kidney failure -- Bone morphogenetic protein signaling in pulmonary arterial hypertension -- BMP signaling in fibrodysplasia ossificans progressiva, a rare genetic disorder of heterotopic ossification -- The central role of BMP signaling in regulating iron homeostasis -- BMPs in inflammation -- Physiological and pathological consequences of vascular BMP signaling -- Bone morphogenetic proteins in the initiation and progression of breast cancer.
  • Digital/Print
    Amir Hussain, Igor Aleksander, Leslie S. Smith ... [et al.], editors.
    Digital : Springer2010
    Print2010
  • Digital
    Conrad Bessant, Darren Oakley, Ian Shadforth.
    OSO2014
    Chapter 1. Introduction -- Chapter 2. Building biological databases with SQL -- Chapter 3. Beginning programming in Perl -- Chapter 4. Analysis and visualisation of data using R -- Chapter 5. Developing web resources -- Chapter 6. Software engineering for bioinformatics.
  • Digital
    Eric Sayers and David Wheeler.
    NCBI Bookshelf2005
    Presents strategies for the use of PubMed.
  • Digital
    edited by Graham Dellaire, Jason N. Berman, Robert J. Arceci.
    ScienceDirect2014
    Cancer Genomics addresses how recent technological advances in genomics are shaping how we diagnose and treat cancer. Built on the historical context of cancer genetics over the past 30 years, the book provides a snapshot of the current issues and state-of-the-art technologies used in cancer genomics. Subsequent chapters highlight how these approaches have informed our understanding of hereditary cancer syndromes and the diagnosis, treatment and outcome in a variety of adult and pediatric solid tumors and hematologic malignancies. The dramatic increase in cancer genomics research and ever-increasing availability of genomic testing are not without significant ethical issues, which are addressed in the context of the return of research results and the legal considerations underlying the commercialization of genomic discoveries. Finally, the book concludes with "Future Directions", examining the next great challenges to face the field of cancer genomics, namely the contribution of non-coding RNAs to disease pathogenesis and the interaction of the human genome with the environment. Tools such as sidebars, key concept summaries, a glossary, and acronym and abbreviation definitions make this book highly accessible to researchers from several fields associated with cancer genomics.Contributions from thought leaders provide valuable historical perspective to relate the advances in the field to current technologies and literature.
  • Digital
    Ulrich Pfeffer, editor.
    Springer2013
    Genomic Pathology of Lung Cancer / Kenneth J. Craddock, Shirley Tam, Chang-Qi Zhu, Ming-Sound Tsao -- Understanding Melanoma Progression by Gene Expression Signatures / J. Tímár, T. Barbai, B. Győrffy, E. Rásó -- Prognostic Testing in Uveal Melanoma / Michael Zeschnigk, Dietmar R. Lohmann -- Capturing and Deciphering the Molecular Signatures of Head and Neck Cancer / Thomas J. Belbin, Roberto A. Lleras, Richard V. Smith -- Predictive and Prognostic Biomarkers for Colorectal Cancer / Lara Lipton, Michael Christie, Oliver Sieber -- Expression Profiling of Hepatocellular Carcinoma / Rosina Maria Critelli, Elisabetta Cariani, Erica Villa -- Kidney Cancer Genomics: Paving the Road to a New Paradigm of Personalized Medicine / George M. Yousef, Nicole M. A. White, Andrew H. Girgis -- Pancreatic Cancer Genomics / Vincenzo Corbo, Andrea Mafficini, Eliana Amato, Aldo Scarpa -- Breast Cancer Genomics: From Portraits to Landscapes / Ulrich Pfeffer, Valentina Mirisola, Alessia Isabella Esposito -- Genomic Landscape of Ovarian Cancer / Delia Mezzanzanica, Loris De Cecco, Marina Bagnoli, Patrizia Pinciroli -- Genetics of Endometrial Carcinoma / M. Angeles López-García, Begoña Vieites, M. Angeles Castilla -- Usefulness of Molecular Biology in Follicular-Derived Thyroid Tumors: From Translational Research to Clinical Practice / Alexandre Bozec, Marius Ilie, Paul Hofman -- Sarcomas Genetics: From Point Mutation to Complex Karyotype, from Diagnosis to Therapies / Frédéric Chibon, Alain Aurias, Jean-Michel Coindre -- Novel Molecular Acquisitions in Leukemias / Sabina Chiaretti, Robin Foà -- Where Do We Stand in the Genomics of Lymphomas? / Francesco Bertoni, Zhi-Ming Li, Emanuele Zucca -- The Genomics of Multiple Myeloma and Its Relevance in the Molecular Classification and Risk Stratification of the Disease / Antonino Neri, Luca Agnelli -- Genome-Wide Analysis and Gene Expression Profiling of Neuroblastoma: What Contribution Did They Give to the Tumor Treatment? / Gian Paolo Tonini.
  • Digital
    edited by Louise von Stechow.
    Springer2018
    This book comprises protocols describing systems biology methodologies and computational tools.
  • Digital
    Alfredo Cesario, Frederick B. Marcus, editors.
    Springer2011
    pt. 1. Introduction and background -- pt. 2. Laboratory, clinical, data and educational resources -- pt. 3. Bioinformatics and systems biology analysis -- pt. 4. Diagnosis, clinical and treatment applications -- pt. 5. Perspectives and conclusions.
  • Digital
    Jeremy J. Shen.
    In this thesis, we present advancements in some change-point problems and their applications to genomic problems that arises from massively parallel sequencing. Change-point problems are concerned with abrupt changes in the generating distribution of a stochastic process evolving over time, space, or any ordered set. This thesis focuses on a number of change-point models and inference problems on point processes. We provide a change-point model and efficient algorithms to detect change-points in relative intensity of non-homogeneous Poisson processes. A model selection approach is constructed in the spirit of classical Baysian Information Criterion, but tailored to the irregularity of change-point problems. We review an array of inference problems surrounding the change-point construct; and propose a point-wise Bayesian credible interval for the parameter of the generating distribution for exponential family. An asymptotic result on the relationship between frequentist and Baysian change-point estimator is shown. We investigate how data characteristics, such as sample size, signal strength, and change-point location, influences the inference procedures through a simulation study. On the application front, modern massively parallel sequencing generates enormous and rich data with much systematic and random noise. We provide a survey of the sequencing technologies and some statistical challenges in various steps of sequencing data analysis. A recent application of sequencing in population and tumor genomics is the profiling of genome copy number and detection of copy number variations across sample. We demonstrate in this thesis that sequencing reads can be viewed naturally as a stochastic process along the genome. Copy number variants are modeled as abrupt jumps in the read intensity function. This modeling assumption resembles the biological reality of mutations that leads to copy number change. We demonstrate the application of change-point methods on actual sequencing data. Our method is found to compare favorably against a commonly used existing method in a spike-in simulation study. We lastly discuss a direction in which our change-point methods can be extended. It is often of interest to find recurrent copy number variants among a collection of biological samples. We review existing array-based multi-sample copy number profiling methods. Estimation and model selection procedures for the multi-sample sequencing setting are derived as extensions of our two-sample methods. A key challenge is the treatment of carrier status, which is whether a sample carries the recurrent variant of question. We present two sets of methods, one based on the assumption that all samples are carriers and the other based on a known carrier set. The statistical characteristics of the two methods are compared in a number of simulation scenarios.
  • Digital
    Mark Anthony Sellmyer.
    A detailed understanding of living systems requires tools to examine and manipulate biological processes. Small molecules and optical imaging technologies are uniquely suited for this purpose. Small molecules enable the specific manipulation of biomolecular targets, and optical imaging permits the real-time observation of molecular and cellular processes in vivo. This dissertation describes a combination of chemical tool development and imaging strategies to address the following biological problems: 1) specific modification of the genome 2) exquisite control of protein function 3) observing cell-cell interactions in living animals. Chapter One describes a technology for targeted gene modification via the induction of double strand breaks in genomic DNA. The chapter begins with an overview of the field of gene targeting, and documents the design, synthesis, and testing of a novel method for high efficiency homologous recombination. The method relies on engineering two reagents, a small molecule DNA targeting element and a nuclease fusion protein. The targeting element, a peptide nucleic acid (PNA), was designed and synthesized to target DNA via Watson-Crick base pairing. The PNA also was covalently linked to the small molecule, trimethoprim, to recruit a DHFR nuclease fusion protein to a specific DNA site. Our studies show that the individual interactions of PNA/DNA and of PNA/nuclease can readily occur. Further, the ternary complex of PNA, DNA, and nuclease can form in solution. Chapters Two, Three, and Four describe the development and further characterization of a general method to perturb protein stability and function. Briefly, an unstable protein domain, termed a destabilizing domain (DD), can confer instability to a fused protein of interest and promote its rapid degradation. This instability can be rescued by the addition of a small molecule, Shield-1. Our work in Chapter Two describes the use of this system to regulate protein function in living mammals. In one example, we show that regulation of a secreted protein, the immunomodulatory cytokine IL-2, can control tumor burden in mouse models. Additionally, we used the DD to control the function of TNF-[Alpha] after systemic delivery to a tumor. Chapter Three expands on these in vivo efforts by employing the system to regulate secreted FGF2, an important modulator of bone formation, for skeletal tissue engineering. Shield-1 induction of FGF2 causes induction of bone formation in a calvarial-defect model. Chapter Four presents our observations on the behavior of the DD in various cellular environments --the cytoplasm, nucleus, endoplasmic reticulum, and mitochondria- and in the presence of small molecules that modulate protein production, degradation, and local protein quality control machinery. These data indicate that the levels of the DD, in the presence and absence ligand, is dependent on its subcellular locale and protein homeostasis machinery. The fifth chapter of this dissertation reports the development of a method to assess spatiotemporal cell-cell relationships in real-time and in living animals. The method is based on small-molecule diffusion of an activatable substrate between two populations of cells, thus allowing assessment of cell-cell proximity in vivo via bioluminescence imaging. One cell population catalyzes the release of a caged luciferin. The free luciferin can diffuse to a nearby population of cells expressing luciferase capable of light-emitting catalysis. Thus the luciferase cells in closest proximity to the "pool" of free luciferin emit the most light. We demonstrate the utility of this system in vitro and in vivo and are currently investigating its use for the detection of cancer and early metastatic disease in mouse models.
  • Digital
    Andras Falus, editor.
    Springer2009
  • Digital
    edited by Ronald J.A. Trent.
    Springer2014
    From the phenotype to the genotype via bioinformatics / Cali E. Willet and Claire M. Wade -- Production and analytic bioinformatics for next-generation DNA sequencing / Richard James Nigel Allcock -- Analyzing the metabolome / Francis G. Bowling and Mervyn Thomas -- Statistical perspectives for genome-wide association studies (GWAS) / Jennifer H. Barrett, John C. Taylor, and Mark M. Iles -- Bioinformatics challenges in genome-wide association studies (GWAS) / Rishika De, William S. Bush, and Jason H. Moore -- Studying cancer genomics through next-generation DNA sequencing and bioinformatics / Maria A. Doyle [and others] -- Using bioinformatics tools to study the role of microRNA in cancer / Fabio Passetti [and others] -- Chromosome microarrays in diagnostic testing : interpreting the genomic data / Greg B. Peters and Mark D. Pertile -- Bioinformatics approach to understanding interacting pathways in neuropsychiatric disorders / Ali Alawieh [and others] -- Pathogen genome bioinformatics / Vitali Sintchenko and Michael P.V. Roper -- Setting up next-generation sequencing in the medical laboratory / Bing Yu -- Managing incidental findings in exome sequencing for research / Marcus J. Hinchcliffe -- Approaches for classifying DNA variants found by sanger sequencing in a medical genetics laboratory / Pak Leng Cheong and Melody Caramins -- Designing algorithms for determining significance of DNA missense changes / Sivakumar Gowrisankar and Matthew S. Lebo -- DNA variant databases : current state and future directions / John-Paul Plazzer and Finlay Macrae -- Natural language processing in biomedicine : a unified system architecture overview / Son Doan [and others] -- Candidate gene discovery and prioritization in rare diseases / Anil G. Jegga -- Computer-aided drug designing / Mohini Gore and Neetin S. Desai.
  • Digital
    edited by Martin Giera.
    Springer2018
    This detailed volume presents a comprehensive compendium of clinical metabolomics protocols covering LC-MS, GC-MS, CE-MS, and NMR-based clinical metabolomics as well as bioinformatics and study design considerations. The methodologies explored here form the core of several very promising initiatives evolving around personalized health care and precision medicine, which can be seen as complimentary to the field of clinical chemistry and aid the aforementioned field with novel disease markers and diagnostic patterns. Written for the highly successful Methods in Molecular Biology series, chapters include brief introductions to their topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.uthoritative and practical, Clinical Metabolomics: Methods and Protocols aims to serve as the basis for successful communication between scientists from several fields, including chemists, biologist, bioinformaticians, and clinicians, ultimately leading to effective study design and completion.
  • Digital
    Vimla L. Patel, Thomas G. Kannampallil, David R. Kaufman, editors.
    Springer2015
  • Digital
    Vimla L. Patel, David R. Kaufman, Trevor Cohen, editors.
    Springer2014
    "Enormous advances in information technology have permeated essentially all facets of life in the past two decades. Formidable challenges remain in fostering tools that enhance productivity but are sensitive to work practices. Cognitive Informatics (CI) is the multidisciplinary study of cognition, information and computational sciences that investigates all facets of human computing including design and computer-mediated intelligent action, thus is strongly grounded in methods and theories from cognitive science. As an applied discipline, it has a close affiliation with human factors and human-computer interaction, and provides a framework for the analysis and modeling of complex human performance in technology-mediated settings and contributes to the design and development of better information systems. In recent years, CI has emerged as a distinct area with special relevance to biomedicine and health care. In addition, it has become a foundation for education and training of health informaticians, the Office of the National Coordinator for Health Information Technology initiating a program including CI as one of its critical elements to support health IT curriculum development. This book represents a first textbook on cognitive informatics and will focus on key examples drawn from the application of methods and theories from CI to challenges pertaining to the practice of critical-care medicine (CCM). Technology is transforming critical care workflows and re-organizing patient care management processes. CCM has proven to be a fertile test bed for theories and methods of cognitive informatics. CI, in turn, has contributed much to our understanding of the factors that result in complexity and patient errors. The topic is strongly interdisciplinary and will be important for individuals from a range of academic and professional backgrounds, including critical care specialists, psychologists, computer scientists, medical informaticians, and anthropologists"--Provided by publisher.
  • Digital
    Xuhua Xia.
    Springer2013
    This book provides an evolutionary conceptual framework for comparative genomics, with the ultimate objective of understanding the loss and gain of genes during evolution, the interactions among gene products, and the relationship between genotype, phenotype and the environment. The many examples in the book have been carefully chosen from primary research literature based on two criteria: their biological insight and their pedagogical merit. The phylogeny-based comparative methods, involving both continuous and discrete variables, often represent a stumbling block for many students entering the field of comparative genomics. They are numerically illustrated and explained in great detail. The book is intended for researchers new to the field, i.e., advanced undergraduate students, postgraduates and postdoctoral fellows, although professional researchers who are not in the area of comparative genomics will also find the book informative.
  • Digital
    edited by João C. Setubal, Jens Stoye, Peter F. Stadler.
    Springer2018
    Gene phylogenies and orthologous groups / Joao C. Setubal and Peter F. Stadler -- Pan-genome storage and analysis techniques / Tina Zekic, Guillaume Holley, and Jens Stoye -- Comparative genomics for prokaryotes / Joao C. Setubal, Nalvo F. Almeida, and Alice R. Wattam -- Assembly, annotation, and comparative genomics in PATRIC, the all bacterial bioinformatics resource center / Alice R. Wattam, Thomas Brettin, James J. Davis, Svetlana Gerdes, Ronald Kenyon, Dustin Machi, Chunhong Mao, Robert Olson, Ross Overbeek, Gordon D. Pusch, Maulik P. Shukla, Rick Stevens, Veronika Vonstein, Andrew Warren, Fangfang Xia, and Hyunseung Yoo -- Phylogenomics / Jose S.L. Patane, Joaquim Martins-JR, and Joao C. Setubal -- Comparative genome annotation / Stefanie Konig, Lars Romoth, and Mario Stanke -- Practical guide for comparative genomics of mobile genetic elements in prokaryotic genomes / Danillo Oliveira Alvarenga, Leandro M. Moreira, Mick Chandler, and Alessandro M. Varani -- Comparative metagenomics / Andrew Maltez Thomas, Felipe Prata Lima, Livia Maria Silva Moura, Aline Maria da, Silva, Emmanuel Dias Neto, and Joao C. Setubal -- Genome rearrangement analysis : cut and join genome rearrangements and gene cluster preserving approaches / Tom Hartmann, Martin Middendorf, and Matthias Bernt -- Whole genome duplication in plants : implications for evolutionary analysis / David Sankoff and Chunfang Zheng -- Sequence-based synteny analysis of multiple large genomes / Daniel Doerr and Bernard M.E. Moret -- Family-free genome comparison / Daniel Doerr, Pedro Feijao, and Jens Stoye -- Comparative methods for reconstructing ancient genome organization / Yoann Anselmetti, Nina Luhmann, Severine Berard, Eric Tannier, and Cedric Chauve -- Comparative RNA genomics / Rolf Backofen, Jan Gorodkin, Ivo L. Hofacker, and Peter F. Stadler -- Bioinformatic approaches for comparative analysis of viruses / Deyvid Amgarten and Chris Upton -- Comparative genomics of gene loss and gain in Caenorhabditis and other nematodes / Christian Rodelsperger -- Comparative genomics in Drosophila / Martin Oti, Attilio Pane, and Michael Sammeth -- Comparative genomics in Homo sapiens / Martin Oti and Michael Sammeth.
  • Digital
    Yoram Vodovotz, Gary An, editors.
    Springer2013
    An overview of the translational dilemma and the need for translational systems biology of inflammation / Yoram Vodovotz and Gary An -- Part I: Complex systems methods and applications. Translational equation-based modeling / Gilles Clermont ; Agent-based modeling in translational systems biology / Scott Christley and Gary An ; Analysis of heart rate variability / Patrick R. Norris ; Analysis of ventilatory pattern variability / Thomas E. Dick [and seven others] -- Part II. Translational modeling of sepsis and trauma. Disorder of systemic inflammation in sepsis and trauma: a systems perspective / Kent R. Zettel II and Timothy R. Billiar ; Multi-scale equation-based models: insights for inflammation and physiological variability / Jeremy D. Scheff ; Integrating data driven and mechanistic models of the inflammatory response in sepsis and trauma / Nabil Azhar [and five others] ; In silico trials and personalized therapy for sepsis and trauma / Yoram Vodovotz, John Bartels, and Gary An -- Part III: Translational modeling of wound healing. Disorder of localized inflammation in wound healing: a systems perspective / Sashwati Roy, Amitava Das, and Chandan K. Sen ; Equation-based models of wound healing and collective cell migration / Julia Arciero and David Swigon ; Agent-based models of wound healing / Jordan R. Stern [and three others] -- Part IV: Translational modeling of host-pathogen interactions. Modeling host-pathogen interactions in necrotizing enterocolitis / Julia Arciero, Jared Barber, and Moses Kim ; Modeling host-vector-pathogen immuno-inflammatory interactions in malaria / Yoram Vodovotz [and nine others] -- Part V: Future perspectives : translation to implementation. The rationale and implementation of translational systems biology as a new paradigm for the study of inflammation / Gary An and Yoram Vodovotz -- Index.
  • Digital
    Andrew E. Teschendorff, editor.
    Springer2015
    This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.
  • Digital
    Noah Zimmerman.
    Changes in frequency and/or biomarker expression in small subsets of peripheral blood cells provide key diagnostics for disease presence, status and prognosis. At present, flow cytometry instruments that measure the joint expression of up to 20 markers in/on large numbers of individual cells are used to measure surface and internal marker expression. This technology is routinely used to determine the frequencies of various marker-defined cell subsets in patient samples and is often used to inform therapeutic decision-making. Nevertheless, quantitative methods for comparing data between samples are sorely lacking. There are no reliable computational methods for determining the magnitude of differences among samples from different patients, among samples obtained from the same patient on different days, or between aliquots of the same sample measured before and after response to stimulation or other treatment. This thesis describes novel computational methods that provide reliable indices of change in subset representation and/or marker expression by individual subsets of cells. The methods we have developed utilize a non-parametric clustering algorithm, Density-Based Merging (DBM), that we developed to identify subsets (clusters) of cells that express a common set of markers measured independently for each cell by flow cytometry. To quantitate differences between these subsets, we introduce the application of Earth Movers Distance (EMD), an algorithm used to compare multivariate distributions borrowed from the image retrieval literature. The resultant methods are highly sensitive and reliable for identifying small marker expression differences between subset of cells in flow cytometry data sets. We show that these methods are easily applied and readily interpreted. Importantly, we demonstrate their practical utility with data from an allergy study in which the expression of two markers on very rare blood cells (basophils) in response to stimulation with an offending allergen indicates whether the patient is allergic to the stimulating antigen. In addition, we have developed novel evaluation criteria for assessing the performance of clustering algorithms on flow cytometry data by combining mixtures of cells identifiable by dimensions "hidden" from the algorithm that provide true cluster membership. Thus, we expect that the methods described here will introduce a new approach to using flow cytometry to measure biomarker changes as indices of drug response, disease susceptibility, disease progress and prognosis.
  • Digital
    edited by Gregory A. Voth.
    ScienceDirectPt. A
    ScienceDirectPt. B
  • Digital
    edited by David Fenyö.
    Springer2010
    Sequencing and genome assembly using next-generation technologies -- RNA structure prediction -- Normalization of gene-expression microarray data -- Prediction of transmembrane topology and signal peptide given a protein's amino acid sequence -- Protein structure modeling -- Template-based protein structure modeling -- Automated protein NMR structure determination in solution -- Computational tools in protein crystallography -- 3-D structures of macromolecules using single-particle analysis in eman -- Computational design of chimeric protein libraries for directed evolution -- Mass spectrometric protein identification using the global proteome machine -- Unbiased detection of posttranslational modifications using mass spectrometry -- Protein quantitation using mass spectrometry -- Modeling experimental design for proteomics -- A functional proteomic study of the Trypanosoma brucei nuclear pore complex: An informatic strategy -- Inference of signal transduction networks from double causal evidence -- Reverse engineering gene regulatory networks related to quorum sensing in the plant pathogen pectobacterium atrosepticum -- Parameter inference and model selection in signaling pathway models -- Genetic algorithms and their application to in silico evolution of genetic regulatory networks.
  • Digital
    Röbbe Wünschiers.
    Springer2013
    This greatly expanded 2nd edition provides a practical introduction to - data processing with Linux tools and the programming languages AWK and Perl- data management with the relational database system MySQL, and- data analysis and visualization with the statistical computing environment R for students and practitioners in the life sciences. Although written for beginners, experienced researchers in areas involving bioinformatics and computational biology may benefit from numerous tips and tricks that help to process, filter and format large datasets. Learning by doing is the basic concept of this book. Worked examples illustrate how to employ data processing and analysis techniques, e.g. for - finding proteins potentially causing pathogenicity in bacteria, - supporting the significance of BLAST with homology modeling, or- detecting candidate proteins that may be redox-regulated, on the basis of their structure. All the software tools and datasets used are freely available. One section is devoted to explaining setup and maintenance of Linux as an operating system independent virtual machine. The author's experiences and knowledge gained from working and teaching in both academia and industry constitute the foundation for this practical approach.
  • Digital
    Tuan Pham, editor.
    Springer2009
    Identification of Relevant Genes from Microarray Experiments based on Partial Least Squares Weights: Application to Cancer Genomics -- Geometric Biclustering and Its Applications to Cancer Tissue Classification Based on DNA Microarray Gene Expression Data -- Statistical Analysis on Microarray Data: Selection of Gene Prognosis Signatures -- Agent-Based Modeling of Ductal Carcinoma In Situ: Application to Patient-Specific Breast Cancer Modeling -- Multicluster Class-Based Classification for the Diagnosis of Suspicious Areas in Digital Mammograms -- Analysis of Cancer Data Using Evolutionary Computation -- Analysis of Population-Based Genetic Association Studies Applied to Cancer Susceptibility and Prognosis -- Selected Applications of Graph-Based Tracking Methods for Cancer Research -- Recent Advances in Cell Classification for Cancer Research and Drug Discovery -- Computational Tools and Resources for Systems Biology Approaches in Cancer -- Laser Speckle Imaging for Blood Flow Analysis -- The Challenges in Blood Proteomic Biomarker Discovery.
  • Digital
    edited by Istvan Ladunga.
    Springer2010
    An overview of the computational analyses and discovery of transcription factor binding sites -- Components and mechanisms of regulation of gene expression -- Regulatory regions in DNA: promoters, enhancers, silencers, and insulators -- Three-dimensional structures of DNA-bound transcriptional regulators -- Identification of promoter regions and regulatory sites -- Motif discovery using expectation maximization and Gibbs' sampling -- Probabilistic approaches to transcription factor binding site prediction -- The motif tool assessment platform (MTAP) for sequence-based transcription factor binding site prediction tools -- Computational analysis of ChIP-seq data -- Probabilistic peak calling and controlling false discovery rate estimations in transcription factor binding site mapping from ChIP-seq -- Sequence analysis of chromatin immunoprecipitation data for transcription factors -- Inferring protein-DNA interaction parameters from SELEX experiments -- Kernel-based identification of regulatory modules -- Identification of transcription factor binding sites derived from transposable element sequences using ChIP-seq -- Target gene identification via nuclear receptor binding site prediction -- Computing chromosome conformation -- Large-scale identification and analysis of C-proteins -- Evolution of cis-regulatory sequences in drosophila -- Regulating the regulators: modulators of transcription factor activity -- Annotating the regulatory genome -- Computational identification of plant transcription factors and the construction of the plant TFDB database -- Practical computational methods for regulatory genomics: a cisGRN-lexicon and cisGRN-browser for gene regulatory networks -- Reconstructing transcriptional regulatory networks using three-way mutual information and Bayesian networks -- Computational methods for analyzing dynamic regulatory networks
  • Digital
    edited by Louise von Stechow, Alberto Santos Delgado.
    Springer2018
    Rule-based models and applications in biology / Álvaro Bustos, Ignacio Fuenzalida, Rodrigo Santibáñez,Tomás Pérez-Acle, and Alberto J.M. Martin -- Optimized protein-protein interaction network usage with context filtering / Natalia Pietrosemoli and Maria Pamela Dobay -- SignaLink : multilayered regulatory networks / Luca Csabai, Márton Ölbei, Aidan Budd, Tamás Korcsmáros, and Dávid Fazekas -- Interplay between long noncoding RNAs and microRNAs in cancer / Francesco Russo, Giulia Fiscon, Federica Conte, Milena Rizzo, Paola Paci, and Marco Pellegrini -- Methods and tools in genome-wide association studies / Anja C. Gumpinger, Damian Roqueiro, Dominik G. Grimm, and Karsten M. Borgwardt -- Identifying differentially expressed genes using fluorescence-activated cell sorting (FACS) and RNA sequencing from low input samples / Natalie M. Clark, Adam P. Fisher, and Rosangela Sozzani -- Computational and experimental approaches to predict host-parasite protein-protein interactions / Yesid Cuesta-Astroz and Guilherme Oliveira -- Integrative approach to virus-host protein-protein interactions / Helen V. Cook and Lars Juhl Jensen -- SQUAD method for the qualitative modeling of regulatory networks / Akram Méndez, Carlos Ramírez, Mauricio Pérez Martínez, and Luis Mendoza -- miRNet--functional analysis and visual exploration of miRNA-target interactions in a network context / Yannan Fan and Jianguo Xia -- Systems biology analysis to understand regulatory miRNA networks in lung cancer / Meik Kunz, Andreas Pittroff, and Thomas Dandekar -- Spatial analysis of functional enrichment (SAFE) in large biological networks / Anastasia Baryshnikova -- Toward large-scale computational prediction of protein complexes / Simone Rizzetto and Attila Csikász-Nagy -- Computational models of cell cycle transitions / Rosa Hernansaiz-Ballesteros, Kirsten Jenkins, and Attila Csikász-Nagy -- Simultaneous profiling of DNA accessibility and gene expression dynamics with ATAC-Seq and RNA-Seq / David G. Hendrickson, Ilya Soifer, Bernd J. Wranik, David Botstein, and R. Scott McIsaac -- Computational network analysis for drug toxicity prediction / C. Hardt, C. Bauer, J. Schuchhardt, and R. Herwig -- Modeling the epigenetic landscape in plant development / Jose Davila-Velderrain, Jose Luis Caldu-Primo, Juan Carlos Martinez-Garcia, and Elena R. Alvarez-Buylla -- Developing network models of multiscale host responses involved in infections and diseases / Rohith Palli and Juilee Thakar -- Exploring dynamics and noise in gonadotropin-releasing hormone (GnRH) signaling / Margaritis Voliotis, Kathryn L. Garner, Hussah Alobaid, Krasimira Tsaneva-Atanasova, and Craig A. McArdle.
  • Digital
    edited by Riccardo Baron.
    Springer2012
    A molecular dynamics ensemble-based approach for the mapping of druggable binding sites / Anthony Ivetac and J. Andrew McCammon -- Analysis of protein binding sites by computational solvent mapping / David R. Hall, Dima Kozakov, and Sandor Vajda -- Evolutionary trace for prediction and redesign of protein functional sites / Angela Wilkins [and others] -- Information entropic functions for molecular descriptor profiling / Anne Mai Wassermann [and others] -- Expanding the conformational selection paradigm in protein-ligand docking / Guray Kuzu [and others] -- Flexibility analysis of biomacromolecules with application to computer-aided drug design / Simone Fulle and Holger Gohlke -- On the use of molecular dynamics receptor conformations for virtual screening / Sara E. Nichols, Riccardo Baron, and J. Andrew McCammon -- Virtual ligand screening against comparative protein structure models / Hao Fan, John J. Irwin, and Andrej Sali -- AMMOS software : method and application / Tania Pencheva [and others] -- Rosetta ligand docking with flexible XML protocols / Gordon Lemmon and Jens Meiler -- Normal mode-based approaches in receptor ensemble docking / Claudio N. Cavasotto -- Application of conformational clustering in protein-ligand docking / Giovanni Bottegoni, Walter Rocchia, and Andrea Cavalli -- How to benchmark methods for structure-based virtual screening of large compound libraries / Andrew J. Christofferson and Niu Huang -- AGGRESCAN : method, application, and perspectives for drug design / Natalia S. de Groot [and others] -- ATTRACT and PTOOLS : open source programs for protein-protein docking Sebastian Schneider [and others] -- Prediction of interacting protein residues using sequence and structure data / Vedran Franke, Mile Šikić, and Kristian Vlahoviček -- MM-GB/SA rescoring of docking poses / Cristiano R.W. Guimarães -- A case study of scoring and rescoring in peptide docking / Zunnan Huang and Chung F. Wong -- The solvated interaction energy method for scoring binding affinities / Traian Sulea and Enrico O. Purisima -- Linear interaction energy : method and applications in drug design / Hugo Guitiérrez-de-Terán and Johan Åqvist -- Estimation of conformational entropy in protein-ligand interactions : a computational perspective / Anton A. Polyansky, Ruben Zubac, and Bojan Zagrovic -- Explicit treatment of water molecules in data-driven protein-protein docking : the solvated HADDOCKing approach / Panagiotis L. Kastritis, Aalt D.J. van Dijk, and Alexandre M.J.J. Bonvin -- Protein-water interactions in MD simulations : POPS/POPSCOMP solvent accessibility analysis, solvation forces and hydration sites / Arianna Fornili [and others] -- Computing the thermodynamic contributions of interfacial water / Zheng Li and Themis Lazaridis -- Assignment of protonation states in proteins and ligands : combining pKa prediction with hydrogen bonding network optimization / Elmar Krieger [and others] -- Best practices in free energy calculations for drug design / Michael R. Shirts -- Independent-trajectory thermodynamic integration : a practical guide to protein-drug binding free energy calculations using distributed computing / Morgan Lawrenz [and others] -- Free energy calculations from one-step perturbations / Chris Oostenbrink -- Using metadynamics and path collective variables to study ligand binding and induced conformational transitions / Neva Bešker and Francesco L. Gervasio -- Accelerated molecular dynamics in computational drug design / Jeff Wereszczynski and J. Andrew McCammon -- Molecular dynamics applied in drug discovery : the case of HIV-1 protease / Yi Shang and Carlos Simmerling -- Decomposing the energetic impact of drug-resistant mutations : the example of HIV-1 protease-DRV binding / Yufeng Cai and Celia Schiffer -- Guide to virtual screening : application to the Akt phosphatase PHLPP / William Sinko [and others] -- Molecular-level simulation of pandemic influenza glycoproteins / Rommie E. Amaro and Wilfred W. Li -- Homology modeling of cannabinoid receptors : discovery of cannabinoid analogues for therapeutic use / Chia-en A. Chang [and others] -- High-throughput virtual screening lead to discovery of non-peptidic inhibitors of West Nile virus NS3 protease / Danzhi Huang.
  • Digital
    edited by Mohini Gore, Umesh B. Jagtap.
    Springer2018
    Computer-aided drug design : an overview / Alan Talevi -- Prediction of human drug targets and their interactions using machine learning methods : current and future perspectives / Abhigyan Nath, Priyanka Kumari, and Radha Chaube -- Practices in molecular docking and structure-based virtual screening / Ricardo N. dos Santos, Leonardo G. Ferreira, and Adriano D. Andricopulo -- Phylogenetic and other conservation-based approaches to predict protein functional sites / Heval Atas, Nurcan Tuncbag, and Tunca Dogan -- De novo design of ligands using computational methods / Venkatesan Suryanarayanan, Umesh Panwar, Ishwar Chandra, and Sanjeev Kumar Singh -- Molecular dynamics simulation and prediction of druggable binding sites / Tianhua Feng and Khaled Barakat -- Virtual ligand screening using PL-PatchSurfer2, a molecular surface-based protein-ligand docking method / Woong-Hee Shin and Daisuke Kihara -- Fragment-based ligand designing / Shashank P. Katiyar, Vidhi Malik, Anjani Kumari, Kamya Singh, and Durai Sundar -- Molecular dynamics as a tool for virtual ligand screening / Gregory Menchon, Laurent Maveyraud, and Georges Czaplicki -- Building molecular interaction networks from microarray data for drug target screening / Sze Chung Yuen, Hongmei Zhu, and Siu-wai Leung -- Absolute alchemical free energy calculations for ligand binding : a beginner's guide / Matteo Aldeghi, Joseph P. Bluck, and Philip C. Biggin -- Evaluation of protein-ligand docking by cyscore / Yang Cao, Wentao Dai, and Zhichao Miao -- Molecular dynamics simulations of protein-drug complexes : a computational protocol for investigating the interactions of small-molecule therapeutics with biological targets and biosensors / Jodi A. Hadden and Juan R. Perilla -- Prediction and optimization of pharmacokinetic and toxicity properties of the ligand / Douglas E. V. Pires, Lisa M. Kaminskas, and David B. Ascher -- Protein-protein docking in drug design and discovery / Agnieszka A. Kaczor, Damian Bartuzi, Tomasz Maciej Stepniewski, Dariusz Matosiuk, and Jana Selent -- Automated inference of chemical discriminants of biological activity / Sebastian Raschka, Anne M. Scott, Mar Huertas, Weiming Li, and Leslie A. Kuhn -- Computational exploration of conformational transitions in protein drug targets / Benjamin P. Cossins, Alastair D. G. Lawson, and Jiye Shi -- Applications of the NRGsuite and the molecular docking software FlexAID in computational drug discovery and design / Louis-Philippe Morency, Francis Gaudreault, and Rafael Najmanovich -- Calculation of thermodynamic properties of bound water molecules / Ying Yang, Amr H. A. Abdallah, and Markus A. Lill -- Enhanced molecular dynamics methods applied to drug design projects / Sonia Ziada, Abdennour Braka, Julien Diharce, Samia Aci-Seche, and Pascal Bonnet -- AGGRESCAN3D : toward the prediction of the aggregation propensities of protein structures / Jordi Pujols, Samuel Pena-Diaz, and Salvador Ventura -- Computational analysis of solvent inclusion in docking studies of protein-glycosaminoglycan systems / Sergey A. Samsonov -- Understanding G protein-coupled receptor allostery via molecular dynamics simulations : implications for drug discovery / Shaherin Basith, Yoonji Lee, and Sun Choi -- Identification of potential microRNA biomarkers by meta-analysis / Hongmei Zhu and Siu-wai Leung.
  • Digital
    edited by Loo Keat Wei.
    ScienceDirect2019
    Computational epigenetics and disease / Loo Keat Wei -- Computational methods for epigenomic analysis / Ho-Ryun Chung -- Statistical approaches for epigenetic data analysis / Thorsten Dickhaus -- Bioinformatics methodology development for the whole genome bisulfite sequencing / Deqiang Sun -- Data analysis of ChIP-Seq experiments: common practice and recent developments / Qi Zhang -- Computational tools for microRNA target prediction / Nurul-Syakima Ab Mutalib, Siti Aishah Sulaiman and Rahman Jamal -- Integrative analysis of epigenomics data / Cenny Taslim, Stephen L. Lessnick and Simon Lin -- Differential DNA methylation and network analysis in schizophrenia / Huang Kuo Chuan -- Epigenome-wide DNA methylation and histone modification of Alzheimer's disease / Ankush Bansal and Tiratha Raj Singh -- Epigenomic reprogramming in cardiovascular disease / Yang Zhou, Jiandong Liu and Li Qian -- Bioinformatic and biostatistic methods for DNA methylome analysis of obesity / Sarah Amandine Caroline Voisin -- Epigenomics of diabetes mellitus / Ivanka Dimova -- Epigenetic profiling in head and neck cancer / Javed Hussain Choudhury, Sharbadeb Kundu, Fazlur Rahaman Talukdar, Ruhina S. Laskar, Raima Das, Shaheen Laskar, Bishal Dhar, Manish Kumar, Sharad Ghosh, Rosy Mondal, Yashmin Choudhury, Sankar Kumar Shosh -- Epigenome-wide DNA methylation profiles in oral cancer / Raghunath Chatterjee, Shantanab Das, Aditi Chandra, Baidehi Basu -- Computational epigenetics for breast cancer / Juan Xu, Yongsheng Li, Tingting Shao, Xia Li -- Integrative epigenomics of prostate cancer / Madonna Peter, Shivani Kamdar and Bharati Bapat -- Network analysis of epigenetic data for bladder cancer / Bor-Sen Chen -- Epigenome-wide analysis of DNA methylation in colorectal cancer / Nurul-Syakima Ab Mutalib, Rashidah Baharuddin and Rahman Jamal -- Integrative omic analysis of neuroblastoma / Kamalakannan Palanichamy -- Computational analysis of epigenetic modifications in melanoma / Ming Tang and Kunal Rai -- DNA methylome of endometrial cancer / Golnaz Asaadi Tehrani -- Epigenetics and epigenomics analysis for autoimmune diseases / Bhawna Gupta, Kumar Sagar Jaiswal, Arup Shosh, Sunil Kumar Raghav -- Computational epigenetics in lung cancer / S. Babichev, V. Lytvynenko, M. Korobchynskyi, I. Sokur.
  • Digital
    Ozkan Ufuk Nalbantoglu and Khalid Sayood.
    Atypon2011
    Recent advances in development of sequencing technology has resulted in a deluge of genomic data. In order to make sense of this data, there is an urgent need for algorithms for data processing and quantitative reasoning. An emerging in silico approach, called computational genomic signatures, addresses this need by representing global species-specific features of genomes using simple mathematical models. This text introduces the general concept of computational genomic signatures, and it reviews some of the DNA sequence models which can be used as computational genomic signatures. The text takes the position that a practical computational genomic signature consists of both a model and a measure for computing the distance or similarity between models. Therefore, a discussion of sequence similarity/distance measurement in the context of computational genomic signatures is presented. The remainder of the text covers various applications of computational genomic signatures in the areas of metagenomics, phylogenetics and the detection of horizontal gene transfer.
  • Digital
    Zlatko Trajanoski, editor.
    Springer2012
    Bioinformatic Tools for the Search of Disease-Associated Variations / Stefan Coassin, Anita Kloss-Brandstätter and Florian Kronenberg -- Cloud Computing / Bringing Computational Power to Medical Genetics / Lukas Forer, Sebastian Schönherr, Hansi Wei€ensteiner, Günther Specht and Florian Kronenberg, et al. -- High-Throughput Characterization and Comparison of Microbial Communities / Bettina Halwachs, Gregor Gorkiewicz and Gerhard G. Thallinger -- Microarray Meta-Analysis: From Data to Expression to Biological Relationships / Julia Feichtinger, Gerhard G. Thallinger, Ramsay J. McFarlane and Lee D. Larcombe -- Analysis of Labeled Quantitative Mass Spectrometry Proteomics Data / Florian Paul Breitwieser and Jacques Colinge -- Lipidomics, Mass Spectrometry, and Bioinformatics / Jürgen Hartler, Harald C. Köfeler, Christopher J. O. Baker, Ravi Tharakan and Gerhard G. Thallinger -- Protein Sequence-Structure-Function-Network Links Discovered with the ANNOTATOR Software Suite: Application to ELYS/Mel-28 / Georg Schneider, Westley Sherman, Durga Kuchibhatla, Hong Sain Ooi and Fernanda L. Sirota, et al. -- 3D Structure and Drug Design / Kristina Djinović-Carugo and Oliviero Carugo -- Integrating Biomolecular and Clinical Data for Cancer Research: Concepts and Challenges / Pornpimol Charoentong, Hubert Hackl, Bernhard Mlecnik, Gabriela Bindea and Jerome Galon, et al. -- Applied Data Mining: From Biomarker Discovery to Decision Support Systems / M. Osl, M. Netzer, S. Dreiseitl and C. Baumgartner -- Network-Based Methods for Computational Diagnostics by Means of R / Laurin A. J. Mueller, Matthias Dehmer and Frank Emmert-Streib.
  • Digital
    edited by Alexander Heifetz.
    Springer2018
    Current and future challenges in GPCR drug discovery / Sid Topiol -- Characterization of ligand binding to GPCRs through computational methods / Silvana Vasile, Mauricio Esguerra, Willem Jespers, Ana Oliveira, Jessica Sallander, Johan Aqvist, and Hugo Gutierrez-de-Teran -- Breakthrough in GPCR crystallography and its impact on computer-aided drug design / Antonella Ciancetta and Kenneth A. Jacobson -- Structural framework for GPCR chemogenomics : what's in a residue number? / Marton Vass, Albert J. Kooistra, Stefan Verhoeven, David Gloriam, Iwan J.P. de Esch, and Chris de Graaf -- GPCR homology model generation for lead optimization / Christofer S. Tautermann -- GPCRs : what can we learn from molecular dynamics simulations? / Naushad Velgy, George Hedger, and Philip C. Biggin -- Methods of exploring protein-ligand interactions to guide medicinal chemistry efforts / Paul Labute -- Exploring GPCR-ligand interactions with the fragment molecular orbital (FMO) method / Ewa I. Chudyk, Laurie Sarrat, Matteo Aldeghi, Dmitri G. Fedorov, Mike J. Bodkin, Tim James, Michelle Southey, Roger Robinson, Inaki Morao, and Alexander Heifetz -- Molecular basis of ligand dissociation from G protein-coupled receptors and predicting residence time / Dong Guo and Adriaan P. IJzerman -- Methodologies for the examination of water in GPCRs / Andrea Bortolato, Benjamin G. Tehan, Robert T. Smith, and Jonathan S. Mason -- Methods for virtual screening of GPCR targets : approaches and challenges / Jason B. Cross -- Approaches for differentiation and interconverting GPCR agonists and antagonists / Przemysław Miszta, Jakub Jakowiecki, Ewelina Rutkowska Maria Turant, Dorota Latek, and Sławomir Filipek -- Opportunities and challenges in the discovery of allosteric modulators of GPCRs / Damian Bartuzi, Agnieszka A. Kaczor, and Dariusz Matosiuk -- Challenges and opportunities in drug discovery of biased ligands / Ismael Rodrıguez-Espigares, Agnieszka A. Kaczor, Tomasz Maciej Stepniewski, and Jana Selent -- Synergistic use of GPCR modeling and SDM experiments to understand ligand binding / Andrew Potterton, Alexander Heifetz, and Andrea Townsend-Nicholson -- Computational support of medicinal chemistry in industrial settings / Daniel F. Ortwine -- Investigating small-molecule ligand binding to G protein-coupled receptors with biased or unbiased molecular dynamics simulations / Kristen A. Marino and Marta Filizola -- Ligand-based methods in GPCR computer-aided drug design / Paul C.D. Hawkins and Gunther Stahl -- Computational methods used in hit-to-lead and lead optimization stages of structure-based drug discovery / Alexander Heifetz, Michelle Southey, Inaki Morao, Andrea Townsend-Nicholson, and Mike J. Bodkin -- Cheminformatics in the service of GPCR drug discovery / Tim James -- Modeling and deorphanization of orphan GPCRs / Constantino Diaz, Patricia Angelloz-Nicoud, and Emilie Pihan.
  • Digital
    edited by Anand R. Asthagiri, Adam P. Arkin.
    ScienceDirect2012
    Principles of model building : an experimentation-aided approach to development of models for signaling networks / Ambhighainath Ganesan and Andre Levchenko -- Integrated inference and analysis of regulatory networks from multi-level measurements / Christopher S. Poultney, Alex Greenfield, and Richard Bonneau -- Swimming upstream : identifying proteomic signals that drive transcriptional changes using the interactome and multiple "-omics" datasets / Shao-shan Carol Huang and Ernest Fraenkel -- A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness / Paul M. Loriaux and Alexander Hoffmann -- Stochastic modeling of cellular networks / Jacob Stewart-Ornstein and Hana El-Samad -- Quantifying traction stresses in adherent cells / Casey M. Kraning-Rush ... [et al.] -- CellOrganizer : image-derived models of subcellular organization and protein distribution / Robert F. Murphy -- Spatial modeling of cell signaling networks / Ann E. Cowan ... [et al.] -- Stochastic models of cell protrusion arising from spatiotemporal signaling and adhesion dynamics / Erik S. Welf and Jason M. Haugh -- Nonparametric variable selection and modeling for spatial and temporal regulatory networks / Anil Aswani ... [et al.] -- Quantitative models of the mechanisms that control genome-wide patterns of animal transcription factor binding / Tommy Kaplan and Mark D. Biggin -- Computational analysis of live cell images of the Arabidopsis thaliana plant / Alexandre Cunha ... [et al.] -- Multi-scale modeling of tissues using CompuCell3D / Maciej H. Swat ... [et al.] -- Multiscale model of fibrin accumulation on the blood clot surface and platelet dynamics / Zhiliang Xu ... [et al.].
  • Digital
    edited by Mario Andrea Marchisio.
    Springer2015
    Computational protein design methods for synthetic biology -- Computer-aided design of DNA origami structures -- Computational design of RNA parts, devices, and transcripts with kinetic folding algorithms implemented on multiprocessor clusters -- Regulatory RNA design through evolutionary computation and strand displacement -- Programming languages for circuit design -- Kappa rule-based modeling in synthetic biology -- Modular design of synthetic gene circuits with biological parts and pools -- Computationally guided design of robust gene circuits -- Chemical master equation closure for computer-aided synthetic biology -- Feedback loops in biological networks -- Efficient analysis methods in synthetic biology -- Using computational modeling and experimental synthetic perturbations to probe biological circuits -- In silico control of biomolecular processes -- Stochastic modular analysis for gene circuits: Interplay among retroactivity, nonlinearity, and stochasticity -- Distributed model construction with virtual parts -- The synthetic biology open language -- Computational methods for the construction, editing, and error correction of DNA molecules and their libraries.
  • Digital
    Guanglei Xiong.
    Modern anatomical medical imaging technologies, such as computed tomography and magnetic resonance, capture structures of the human body in exquisite detail. Computational anatomy is a developing discipline to extract and characterize the anatomy from images. Unfortunately, anatomical images do not reveal the functional behavior. Computational physiology shows great potential to link the structure-function relationship by considering both the anatomical information and the physical governing laws. The simulated physiology can be used to assess physiological states, and more importantly predict the outcomes of interventions. On the other hand, advances in the functional imaging techniques provide measured physiology information and should be utilized together with computational physiology. In the theme of computational anatomy and physiology, this dissertation describes computational methods of modeling vascular geometry for image-based blood flow computation and tracking pulmonary motion for image-guided radiation therapy. Blood flow computation is a useful tool to quantify in vivo hemodynamics. The essential first step is to model vascular geometry from medical imaging data. I have developed a new workflow for this task. The geometric model construction is based on 3D image segmentation and geometric processing. To represent the topology of the constructed model, I have developed a novel centerline extraction method. To account for compliant vessels, methods to assign spatially-varying mechanical properties of the vessel wall are also developed. The workflow greatly increases the modeling efficiency. The combination of the patient-specific geometry and wall deformation can enhance the fidelity of blood flow simulation. Image-based blood flow computation also holds great promise for device design and surgical procedure evaluation. Next, I have developed novel virtual intervention methods to deploy stents or stent grafts to patient-specific pre-operative geometric models constructed from medical images. These methods enable prospective model construction and may be used to evaluate the outcomes of alternative treatment options. Respiratory motion is closely related to the physiology of the lung. Finally, I have developed a novel framework to track patient-specific pulmonary motion from 4D computed tomography images. A large set of vascular junction structures in the lung are identified as landmarks and tracked to obtain their motion trajectories. This framework can provide accurate motion information, which is important in radiation therapy to reduce healthy tissue irradiation while allowing target dose escalation. This work demonstrates the importance of the geometry and motion modeling tools in computational anatomy and physiology. Accurate physiological information, whether simulated or measured, will benefit the diagnosis and treatment of various diseases.
  • Digital
    edited by Xuedong Liu, Meredith D. Betterton.
    Springer2012
    Predictive models for cellular signaling networks / Dagmar Iber and Georgios Fengos -- Analyzing and constraining signaling networks : parameter estimation for the user / Florian Geier [and others] -- A tutorial on mathematical modeling of biological signaling pathways / Zhike Zi -- Bistability iin one equation or fewer / Graham A. Anderson, Xuedong Liu, and James E. Ferrell, Jr. -- Mathematical investigation of how oncogenic Ras mutants promote Ras signaling / Edward C. Stites and Kodi S. Ravichandran -- Modeling miRNA regulation in cancer signaling systems : miR-34a regulation of the p53/Sirt1 signaling module / Xin Lai, Olaf Wolkenhauer, and Julio Vera -- Design of experiments to investigate dynamic cell signaling models / Samuel Bandara and Tobias Meyer -- Mathematical modeling of biochemical systems with PottersWheel / Thomas Maiwald, Oliver Eberhardt, and Julie Blumberg -- Rule-based modeling of signal transduction : a primer / John A.P. Sekar and James R. Faeder -- Computational modeling of signal transduction networks : a pedagogical exposition / Ashok Prasad -- Modeling spatiotemporal dynamics of bacterial populations / Hao Song and Lingchong You -- Discrete dynamic modeling of signal transduction networks / Assieh Saadatpour and Réka Albert -- Analytic methods for modeling stochastic regulatory networks / Aleksandra M. Walczak, Andrew Mugler, and Chris H. Wiggins.
  • Digital
    Gaurav Chopra.
    Computational structural biology is a field that involves modeling of physical interactions between complex biological macromolecules in the aqueous environment in the cell. We model the solvent (water) environment around biological macromolecules, to better understand the physical interactions needed to improve methods of protein structure prediction and, more generally, for the protein folding problem. In this thesis, we model the effect of solvent environment on protein structure refinement using implicit and explicit water models. Specifically we used the Generalized Born Surface Area (GBSA) implicit water model and the SPC and TIP4P explicit water models with the all-atom OPLS force field. We also used the knowledge-based (KB) statistical potential functions, derived from high-resolution X-ray crystals of protein structures. The KB potentials include the affect of solvent implicitly, in that the distribution of distances between atoms in protein crystals is effected by the water in the unit cell. These potentials and water models were tested for refinement of an extensive set of protein structures, using energy minimization and molecular dynamics. Energy minimization with GBSA outperformed KB potential energy minimization, in that large magnitude of refinement was observed. Energy minimization with KB potential was more consistent, in that it refined more protein structures than GBSA. We also tested our computationally inexpensive KB energy minimization in the refinement category at the eight world-wide experiments on Critical Assessment of techniques for protein Structure Prediction (CASP) that performed well. We performed a consistency test on the all the predicted protein structure models by all groups at CASP that improved streorechemistry and refined models for the best performing groups. This warrants the use of this simple and computationally inexpensive, but consistent refinement protocol to act as a natural "end" step for all participating groups at CASP. Accurate description of the water structure around the solute of interest could improve our understanding of various biological processes such as protein folding. We study the hydration of hydrophobic solutes of varying sizes (methane, benzene, cyclohexane and Buckminsterfullerene) with Molecular Dynamics (MD) simulations using a recently introduced state-of-the-art quantum general purpose quantum mechanical polarizable force field (QMPFF3) fitted solely to high-level quantum mechanical data at MP2/cc-pVTZ level with a simple model correction using CCSD(T) data for higher accuracy of aromatic carbon atom type. We ask how well the hydrophobic affect is represented in classical force fields when compared to a more rigorous quantum mechanical force field. Polarization increases ordered water structure, in that the imprint of the hydrophobic surface extends to long range effect (up to 10Å for Buckminsterfullerene). Similar surface water affects, with less ordering are also observed for classical force fields. Most of the water molecules point their dipole moment away from the hydrophobic solutes but often one OH bond points towards the hydrophobic solute surface. The major conclusion from this study is that a quantum mechanical force field increases the strength of the hydrophobic effect; this could have a profound affect on protein folding.
  • Digital
    Ankur Dhanik.
    Proteins are biomolecules that play a key role in a wide diversity of vital functions, such as metabolism and signal transmission. Each protein is a linear chain of amino acids that folds into a flexible three-dimensional structure. Protein's flexibility is widely believed to be essential for its function. Motion of a protein occurs at timescales that span several orders of magnitude. Thermal fluctuations, which occur in picoseconds, are small-amplitude, uncorrelated, harmonic motions of the individual atoms. In contrast, conformational deformations closely related to the protein's function occur in microseconds to milliseconds. These slow deformations are usually large-scale, correlated, anharmonic motions that correspond to transitions between meta-stable states, such as binding and non-binding states. In this dissertation we are mainly interested in modeling structural heterogeneity associated with such slow deformations. This dissertation presents new computational methods to study the flexibility of folded protein in the context of three important biological problems: (a) Loop sampling, (b) Interpretation of electron density maps, and (c) Determination of allosteric pathways. Computational modeling of structural heterogeneity in the folded state of a protein is a challenging problem, mainly because of the high-dimensionality of the protein's conformation space and the very small relative volume of its feasible motion space. Although our methods are specific to each of the three problems, they share the same sample and select approach: they combine efficient sampling algorithms that allow us to represent structural heterogeneity in a folded protein by a collection of sampled conformations and selection algorithms that allow us to reliably pick the sampled conformations that provide a solution to the problem. This dissertation demonstrates the power of geometric computation and efficient sampling to model structural heterogeneity in the folded protein.
  • Digital
    edited by Dr Ahmed A. Moustafa.
    Wiley2018
    A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. -Covers computational approximations to intellectual disability in down syndrome -Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease -Examines neural circuit models of serotonergic system (from microcircuits to cognition) -Educates on information theory, memory, prediction, and timing in associative learning Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students-as well as researchers involved in computational neuroscience modeling research.
  • Digital
    edited by Matthias Dehmer, Yongtang Shi, and Frank Emmert-Streib.
    Wiley2017
    Using the DiffCorr Package to Analyze and Visualize Differential Correlations in Biological Networks / Atsushi Fukushima, Kozo Nishida -- Analytical Models and Methods for Anomaly Detection in Dynamic, Attributed Graphs / Benjamin A Miller, Nicholas Arcolano, Stephen Kelley, Nadya T Bliss -- Bayesian Computational Algorithms for Social Network Analysis / Alberto Caimo, Isabella Gollini -- Threshold Degradation in R Using iDEMO / Chien-Yu Peng, Ya-Shan Cheng -- Optimization of Stratified Sampling with the R Package SamplingStrata: Applications to Network Data / Marco Ballin, Giulio Barcaroli -- Exploring the Role of Small Molecules in Biological Systems Using Network Approaches / Rajarshi Guha, Sourav Das -- Performing Network Alignments with R / Qiang Huang, Ling-Yun Wu -- ℓ1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields / Luigi Augugliaro, Angelo M Mineo, Ernst C Wit -- Cluster Analysis of Social Networks Using R / Malika Charrad -- Inference and Analysis of Gene Regulatory Networks in R / Ricardo de M Simoes, Matthias Dehmer, Constantine Mitsiades, Frank Emmert-Streib -- Visualization of Biological Networks Using NetBioV / Shailesh Tripathi, Salissou Moutari, Matthias Dehmer, Frank Emmert-Streib.
  • Digital
    edited by Duncan J. MacGregor and Gareth Leng.
    Wiley2016
    Bridging between experiments and equations : a tutorial on modeling excitability / David McCobb and Mary Lou Zeeman -- Ion channels and electrical activity in pituitary cells : a modeling perspective / Richard Bertram, Joel Tabak, and Stanko S. Stojilkovic -- Endoplasmic reticulum- and plasma membrane-driven calcium oscillations / Arthur Sherman -- Mathematical models of GnRH neurons / James Sneyd -- Modeling spiking in the magnocellular vasopressin neuron / Duncan J. MacGregor, and Gareth Leng -- Modeling endocrine cell network topology / David J. Hodson, Francois Molino, and Patrice Mollard -- Modelling the milk-ejection reflex / Gareth Leng and Jianfeng Feng -- Dynamics of the HPA axis : a systems modelling approach / John R. Terry, Jamie J. Walker, Francesca Spiga, and Stafford L. Lightman -- Modeling the dynamics of gonadotropin-releasing hormone (GnRH) secretion in the course of an ovarian cycle / Frederique Clement and Alexandre Vidal.
  • Digital
    Boris Gutkin, Serge H. Ahmed, editors.
    Springer2012
    Pt. 1. Pharmacological-based models of addiction -- pt. 2. Neurocomputational models of addiction -- pt. 3. Economic-based models of addiction.
  • Digital
    edited by Sven Bestmann.
    ScienceDirect2015
    Preface: computational neurostimulation in basic and translational research / Sven Bestmann -- Modeling sequence and quasi-uniform assumption in computational neurostimulation / Marom Bikson, Dennis Q. Truong, Antonios P. Mourdoukoutas, Mohamed Aboseria, Niranjan Khadka, Devin Adair, Asif Rahman -- Multilevel computational models for predicting the cellular effects of noninvasive brain stimulation / Asif Rahman, Belen Lafon, Marom Bikson -- Experiments and models of cortical oscillations as a target for noninvasive brain stimulation / Flavio Fröhlich -- Understanding the nonlinear physiological and behavioral effects of tDCS through computational neurostimulation / James J. Bonaiuto, Sven Bestmann -- Modeling TMS-induced I-waves in human motor cortex / Jochen Triesch, Christoph Zrenner, Ulf Ziemann -- Deep brain stimulation for neurodegenerative disease: A computational blueprint using dynamic causal modeling / Rosalyn Moran -- Model-based analysis and design of waveforms for efficient neural stimulation / Warren M. Grill -- Computational neurostimulation for Parkinson's disease / Simon Little, Sven Bestmann -- Computational modeling of neurostimulation in brain diseases / Yujiang Wang, Frances Hutchings, Marcus Kaiser -- Understanding the biophysical effects of transcranial magnetic stimulation on brain tissue: The bridge between brain stimulation and cognition / Sebastiaan F.W. Neggers, Petar I. Petrov, Stefano Mandija, Iris E.C. Sommer, Nico A.T. van den Berg -- Modeling the effects of noninvasive transcranial brain stimulation at the biophysical, network, and cognitive Level / Gesa Hartwigsen, Til Ole Bergmann, Damian Marc Herz, Steffen Angstmann, Anke Karabanov, Estelle Raffin, Axel Thielscher, Hartwig Roman Siebner.
  • Digital
    Andrew Hanno Beck.
    The medical specialty of pathology is focused on the transformation of information extracted from patient tissue samples into biologically informative and clinically useful diagnoses to guide research and clinical care. Since the mid-19th century, the primary data type used by surgical pathologists has been microscopic images of hematoxylin and eosin stained tissue sections. Over the past several decades, molecular data have been increasingly incorporated into pathological diagnoses. There is now a need for the development of new computational methods to systematically model and integrate these complex data to support the development of data-driven diagnostics for pathology. The overall goal of this dissertation is to develop and apply methods in this new field of Computational Pathology, which is aimed at: 1) The extraction of comprehensive integrated sets of data characterizing disease from a patient's tissue sample; and 2) The application of machine learning-based methods to inform the interpretation of a patient's disease state. The dissertation is centered on three projects, aimed at the development and application of methods in Computational Pathology for the analysis of three primary data types used in cancer diagnostics: 1) morphology; 2) biomarker expression; and 3) genomic signatures. First, we developed the Computational Pathologist (C-Path) system for the quantitative analysis of cancer morphology from microscopic images. We used the system to build a microscopic image-based prognostic model in breast cancer. The C-Path prognostic model outperformed competing approaches and uncovered the prognostic significance of several novel characteristics of breast cancer morphology. Second, to systematically evaluate the biological informativeness and clinical utility of the two most commonly used protein biomarkers (estrogen receptor (ER) and progesterone receptor (PR)) in breast cancer diagnostics, we performed an integrative analysis over publically available expression profiling data, clinical data, and immunohistochemistry data collected from over 4,000 breast cancer patients, extracted from 20 published studies. We validated our findings on an independent integrated breast cancer dataset from over 2,000 breast cancer patients in the Nurses' Health Study. Our analyses demonstrated that the ER-/PR+ disease subtype is rare and non-reproducible. Further, in our genomewide study we identified hundreds of biomarkers more informative than PR for the stratification of both ER+ and ER- disease. Third, we developed a new computational method, Significance Analysis of Prognostic Signatures (SAPS), for the identification of robust prognostic signatures from clinically annotated Omics data. We applied SAPS to publically available clinically annotated gene expression data obtained from over 3,800 breast cancer patients from 19 published studies and over 1,700 ovarian cancer patients from 11 published studies. Using these two large meta-datasets, we applied SAPS and performed the largest analysis of subtype-specific prognostic pathways ever performed in breast or ovarian cancer. Our analyses led to the identification of a core set of prognostic biological signatures in breast and ovarian cancer and their molecular subtypes. Further, the SAPS method should be generally useful for future studies aimed at the identification of biologically informative and clinically useful signatures from clinically annotated Omics data. Taken together, these studies provide new insights into the biological factors driving cancer progression, and our methods and models will support the continuing development of the field of Computational Pathology.
  • Digital
    edited by Peng Zhou, Jian Huang,.
    Springer2015
    De novo peptide structure prediction : an overview / Pierre Thévenet [and three others] -- Molecular modeling of peptides / Krzysztof Kuczera -- Improved methods for classification, prediction, and design of antimicrobial peptides / Guangshun Wang -- Building MHC class II epitope predictor using machine learning approaches / Loan Ping Eng, Tin Wee Tan, and Joo Chuan Tong -- Brownian dynamics simulation of peptides with the University of Houston Brownian Dynamics (UHBD) program / Tongye Shen and Chung F. Wong -- Computational prediction of short linear motifs from protein sequences / Richard J. Edwards and Nicolas Palopoli -- Peptide toxicity prediction / Sudheer Gupta [and five others] -- Synthetic and structural routes for the rational conversion of peptides into small molecules / Pasqualina Liana Scognamiglio, Giancarlo Morelli, and Daniela Marasco -- In silico design of antimicrobial peptides / Giuseppe Maccari, Mariagrazia Di Luca, and Riccardo Nifosì -- Information-driven modeling of protein-peptide complexes / Mikael Trellet, Adrien S.J. Melquiond, and Alexandre M.J.J. Bonvin -- Computational approaches to developing short cyclic peptide modulators of protein-protein interactions / Fergal J. Duffy, Marc Devocelle, and Denis C. Shields -- A use of homology modeling and molecular docking methods : to explore binding mechanisms of nonylphenol and bisphenol A with antioxidant enzymes / Mannu Jayakanthan [and three others] -- Computational peptide vaccinology / Johannes Söllner -- Computational modeling of peptide-aptamer binding / Kristen L. Rhinehardt, Ram V. Mohan, and Goundla Srinivas.
  • Digital
    edited by Defang Ouyang and Sean C. Smith.
    Wiley2015
    Introduction of computational pharmaceutics / Ouyang -- Crystal energy landscapes for aiding crystal form selection / Sarah Price -- Solubilization of poor-soluble drugs in cyclodextron formulation / Ouyang -- Molecular modeling for polymeric and micellar drug delivery / Sharon M.Loverde -- Solid dispersion : a pragmatic method to improve the bioavailability of poorly soluble drugs / Ouyang -- Computer simulations of lipid membranes and liposomes for drug delivery / Becky Notman -- Molecular modeling for protein aggregation and formulation / Jim Warwicker -- Computational simulation of drug delivery by nano-materials at molecular level / Youyong Li -- Molecular and analytical modeling of nanodiamond for drug delivery applications / Amanda Barnard -- Molecular modeling of LDH drug delivery systems / Vinuthaa Murthy -- Molecular dynamics simulation as a tool to study the efficacy of PEGylation / Alex Bunker -- Synchrotron radiation micro computed tomography : a new approach for quantitative 3D structural architecture of drug delivery systems / Jiwen Zhang -- Pharmacokinetic modelling and simulation in drug delivery / Raj.
  • Digital
    edited by Ilan Samish.
    Springer2017
  • Digital
    edited by Alan Anticevic, John D. Murray.
    ScienceDirect2018
    Section I. Applying circuit modeling to understand psychiatric symptoms -- Section II. Modeling neural system disruptions in psychiatric illness -- Section III. Characterizing complex psychiatric symptoms via mathematical models .
  • Digital
    M. V. K. Karthik, Pratyoosh Shukla.
    Springer2012
  • Digital
    edited by Jason McDermott ... [et al.].
    Springer2009
    Part 1. Network components -- 1. Identification of cis-regulatory elements in gene co-expression networks using A-GLAM / Leonardo Mariño-Ramírez ... [et al.] -- 2. Structure-based Ab initio prediction of transcription factor-binding sites / L. Angela Liu and Joel S. Bader -- 3. Inferring protein-protein interactions from multiple protein domain combinations / Simon P. Kanaan ... [et al.] -- 4. Prediction of protein-protein interactions: a study of the co-evolution model / Itai Sharon, Jason V. Davis, and Golan Yona -- 5. Computational reconstruction of protein-protein interaction networks: algorithms and issues / Eric Franzosa, Bolan Linghu, and Yu Xia -- 6. Prediction and integration of regulatory and protein-protein interactions / Duangdao Wichadakul, Jason McDermott, and Ram Samudrala -- 7. Detecting hierarchical modularity in biological networks / Erzsebet Ravasz -- Part 2. Network inference -- 8. Methods to reconstruct and compare transcriptional regulatory networks / M. Madan Babu, Benjamin Lang, and L. Aravind -- 9. Learning global models of transcriptional regulatory networks from data / Aviv Madar and Richard Bonneau -- 10. Inferring molecular interactions pathways from eQTL data / Imran Rashid, Jason McDermott, and Ram Samudrala -- 11. Methods for the inference of biological pathways and networks / Roger E. Bumgarner and Ka Yee Yeung -- Part 3. Network dynamics -- 12. Exploring pathways from gene co-expression to network dynamics / Huai Li, Yu Sun, and Ming Zhan -- 13. Network dynamics / Herbert M. Sauro -- 14. Kinetic modeling of biological systems / Haluk Resat, Linda Petzold, and Michel F. Pettigrew -- 15. Guidance for data collection and computational modelling of regulatory networks / Adam Christopher Palmer, and Keith Edward Shearwin -- Part 4. Function and evolutionary systems biology -- 16. Maximum likelihood method for reconstruction of the evolution of eukaryotic gene structure / Liran Carmel, ... [et al.] -- 17. Enzyme function prediction with interpretable models / Umar Syed and Golan Yona -- 18. Using evolutionary information to find specificity-determining and co-evolving residues / Grigory Kolesov and Leonid A. Mirny -- 19. Connecting protein interaction data, mutations, and disease using bioinformatics / Jake Y. Chen, Eunseog Youn, and Sean D. Mooney -- 20. Effects of functional bias on supervised learning of a gene network model / Insuk Lee and Edward M. Marcotte -- Part 5. Computational infrastructure for systems biology -- 21. Comparing algorithms for clustering of expression data: how to assess gene clusters / Golan Yona, William Dirks, and Shafquat Rahman -- 22. Bioverse API and web application / Michal Guerquin ... [et al.] -- 23. Computational representation of biological systems / Zach Frazier ... [et al.] -- 24. Biological network inference and analysis using SEBINI and CABIN / Ronald Taylor and Mudita Singhal.
  • Digital
    edited by Roland Eils, Andres Kriete.
    ScienceDirect2014
    Introducing computational systems biology / Roland Eils, Andres Kriete -- Structural systems biology : modeling interactions and networks for systems studies / Robert B. Russell, Gordana Apic, Olga Kalinina, Leonardo Trabuco, Matthew J. Betts, Qianhao Lu -- Understanding principles of the dynamic biochemical networks of life through systems biology / Hans V. Westerhoff, Fei He, Ettore Murabito, Frederic Cremazy, Matteo Barberis -- Biological foundations of signal transduction, systems biology and aberrations in disease / Ursula Klingmuller, Marcel Schilling, Sofia Depner, Lorenza A. D'Alessandro -- Complexities in quantitative systems analysis of signaling networks / Christina Kiel, Luis Serrano -- Gene networks : estimation, modeling, and simulation / Seiya Imoto, Hiroshi Matsuno, Satoru Miyano -- Reconstruction of metabolic network from genome information and its structural and functional analysis / Hong-Wu Ma, An-Ping Zeng -- Standards, platforms, and applications / Stanley Gu, Herbert Sauro -- Databases, standards, and modeling platforms for systems biology / Juergen Eils, Elena Herzog, Baerbel Felder, Christian Lawerenz, Roland Eils -- Computational models for circadian rhythms : deterministic versus stochastic approaches / Jean-christophe Leloup, Didier Gonze, Albert Goldbeter -- Top-down dynamical modeling of molecular regulatory networks / Reinhard Laubenbacher, Pedro Mendes -- Discrete gene network models for understanding multicellularity and cell reprogramming : from network structure to attractor landscapes landscape / Joseph Xu Zhou, Xiaojie Qiu, Aymeric Fouquier D'Herouel, Sui Huang -- Stochastic simulations of cellular processes : from single cells to colonies / John Cole, Mike J. Hallock, Piyush Labhsetwar, Joseph R. Peterson, John E. Stone, Zaida Luthey-Schulten -- Advances in machine learning for processing and comparison of metagenomic data / Jean-Luc Bouchot, William L. Trimble, Gregory Ditzler, Yemin Lan, Steve Essinger, Gail Rosen -- Systems biology of infectious diseases and vaccines / Helder I. Nakaya -- From cell behavior to tissue deformation : computational modeling and simulation of early animal embryogenesis with the mecagen platform / Julien Delile, Ren Doursat, Nadine Peyriras -- Developing a systems biology of aging / Andres Kriete, Mathieu Cloutier -- Morphometric analysis of tissue heterogeneity in glioblastoma multiforme -- Applications in cancer research : mathematical models of apoptosis / Stefan M. Kallenberger, Stefan Legewie, Roland Eils.
  • Digital
    edited by Tao Huang.
    Springer2018
    DNA sequencing data analysis / Keyi Long, Lei Cai, and Lin He -- Transcriptome sequencing : RNA-seq / Hong Zhang, Lin He, and Lei Cai -- Capture hybridization of long-range DNA fragments for high-throughput sequencing / Xing Chen, Gang Ni, Kai He, Zhao-Li Ding, Gui-Mei Li, Adeniyi C. Adeola, Robert W. Murphy, Wen-Zhi Wang, and Ya-Ping Zhang -- Introduction and clinical application of cell-free tumor DNA / Jun Li, Renzhong Liu, Cuihong Huang, Shifu Chen, and Mingyan Xu -- Bioinformatics analysis for cell-free tumor DNA sequencing data / Shifu Chen, Ming Liu, and Yanqing Zhou -- Overview of genome-wide association studies / Michelle Chang, Lin He, and Lei Cai -- Integrative analysis of omics big data / Xiang-Tian Yu and Tao Zeng -- Reconstruction and analysis of gene regulatory networks / Guangyong Zheng and Tao Huang -- Differential coexpression network analysis for gene expression data / Bao-Hong Liu -- iSeq : web-based RNA-seq data analysis and visualization / Chao Zhang, Caoqi Fan, Jingbo Gan, Ping Zhu, Lei Kong, and Cheng Li -- Revisit of machine learning supported biological and biomedical studies / Xiang-tian Yu, Lu Wang, and Tao Zeng -- Identifying interactions between long noncoding RNAs and diseases based on computational methods / Wei Lan, Liyu Huang, Dehuan Lai, and Qingfeng Chen -- Survey of computational approaches for prediction of DNA-binding residues on protein surfaces / Yi Xiong, Xiaolei Zhu, Hao Dai, and Dong-Qing Wei -- Computational prediction of protein O-GlcNAc modification / Cangzhi Jia and Yun Zuo -- Machine learning-based modeling of drug toxicity / Jing Lu, Dong Lu, Zunyun Fu, Mingyue Zheng, and Xiaomin Luo -- Metabolomics : a high-throughput platform for metabolite profile exploration / Jing Cheng, Wenxian Lan, Guangyong Zheng, and Xianfu Gao -- Single-cell protein assays : a review / Beiyuan Fan, Junbo Wang, Ying Xu, and Jian Chen -- Data analysis in single-cell transcriptome sequencing / Shan Gao -- Applications of single-cell sequencing for multiomics / Yungang Xu and Xiaobo Zhou -- Progress on diagnosis of tuberculous meningitis / Yi-yi Wang and Bing-di Xie -- Insights of acute lymphoblastic leukemia with development of genomic investigation / Heng Xu and Yang Shu.
  • Digital
    Nicolas Le Novère, editors.
    Springer2012
    Functional Genomics and Molecular Networks Gene Expression Regulations in Complex Diseases: Down Syndrome as a Case Study / Marie-Claude Potier and Isabelle Rivals -- Reconstructing Models from Proteomics Data / Lysimachos Zografos, Andrew J. Pocklington and J. Douglas Armstrong -- Using Chemical Kinetics to Model Neuronal Signalling Pathways / Lukas Endler, Melanie I. Stefan, Stuart J. Edelstein and Nicolas Le Novère -- Breakdown of Mass-Action Laws in Biochemical Computation / Fidel Santamaria, Gabriela Antunes and Erik De Schutter -- Spatial Organization and Diffusion in Neuronal Signaling / Sherry-Ann Brown, Raquell M. Holmes and Leslie M. Loew -- The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model / Richard Naud and Wulfram Gerstner -- Multi-compartmental Models of Neurons / Upinder S. Bhalla -- Noise in Neurons and Other Constraints / A. Aldo Faisal -- Methodological Issues in Modelling at Multiple Levels of Description / Kevin Gurney and Mark Humphries -- Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers / Anders Lansner and Markus Diesmann -- Co-operative Populations of Neurons: Mean Field Models of Mesoscopic Brain Activity / David T. J. Liley, Brett L. Foster and Ingo Bojak -- Cellular Spacing: Analysis and Modelling of Retinal Mosaics / Stephen J. Eglen -- Measuring and Modeling Morphology: How Dendrites Take Shape / Todd A. Gillette and Giorgio A. Ascoli -- Axonal Growth and Targeting / Duncan Mortimer, Hugh D. Simpson and Geoffrey J. Goodhill -- Encoding Neuronal Models in SBML / Sarah M. Keating and Nicolas Le Novère -- NeuroML / Padraig Gleeson, Volker Steuber, R. Angus Silver and Sharon Crook -- XPPAUT / Bard Ermentrout -- NEST by Example: An Introduction to the Neural Simulation Tool NEST / Marc-Oliver Gewaltig, Abigail Morrison and Hans Ekkehard Plesser.
  • Digital
    edited by Orazio Nicolotti.
    Springer2018

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