Biological Sequence Analysis

Probabilistic Models of Proteins and Nucleic Acids

Author: Richard Durbin,Sean R. Eddy,Anders Krogh,Graeme Mitchison

Publisher: Cambridge University Press

ISBN: 113945739X

Category: Science

Page: N.A

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Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
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Introduction to Computational Biology

Maps, Sequences and Genomes

Author: Michael S. Waterman

Publisher: CRC Press

ISBN: 9780412993916

Category: Mathematics

Page: 448

View: 8035

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Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.
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Handbook of Statistical Genetics

Author: David J. Balding,Martin Bishop,Chris Cannings

Publisher: John Wiley & Sons

ISBN: 9780470997628

Category: Science

Page: 1616

View: 918

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The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the handbook contains a much expanded section on Network Modeling, including 5 new chapters covering metabolic networks, graphical modeling and inference and simulation of pedigrees and genealogies. Other chapters new to the 3rd edition include Human Population Genetics, Genome-wide Association Studies, Family-based Association Studies, Pharmacogenetics, Epigenetics, Ethic and Insurance. As with the second Edition, the Handbook includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between the chapters, tying the different areas together. With heavy use of up-to-date examples, real-life case studies and references to web-based resources, this continues to be must-have reference in a vital area of research. Edited by the leading international authorities in the field. David Balding - Department of Epidemiology & Public Health, Imperial College An advisor for our Probability & Statistics series, Professor Balding is also a previous Wiley author, having written Weight-of-Evidence for Forensic DNA Profiles, as well as having edited the two previous editions of HSG. With over 20 years teaching experience, he’s also had dozens of articles published in numerous international journals. Martin Bishop – Head of the Bioinformatics Division at the HGMP Resource Centre As well as the first two editions of HSG, Dr Bishop has edited a number of introductory books on the application of informatics to molecular biology and genetics. He is the Associate Editor of the journal Bioinformatics and Managing Editor of Briefings in Bioinformatics. Chris Cannings – Division of Genomic Medicine, University of Sheffield With over 40 years teaching in the area, Professor Cannings has published over 100 papers and is on the editorial board of many related journals. Co-editor of the two previous editions of HSG, he also authored a book on this topic.
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Computational Intelligence and Pattern Analysis in Biology Informatics

Author: Ujjwal Maulik,Sanghamitra Bandyopadhyay,Jason T. Wang

Publisher: John Wiley & Sons

ISBN: 1118097807

Category: Medical

Page: 372

View: 1006

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An invaluable tool in Bioinformatics, this unique volume providesboth theoretical and experimental results, and describes basicprinciples of computational intelligence and pattern analysis whiledeepening the reader's understanding of the ways in which theseprinciples can be used for analyzing biological data in anefficient manner. This book synthesizes current research in the integration ofcomputational intelligence and pattern analysis techniques, eitherindividually or in a hybridized manner. The purpose is to analyzebiological data and enable extraction of more meaningfulinformation and insight from it. Biological data for analysisinclude sequence data, secondary and tertiary structure data, andmicroarray data. These data types are complex and advanced methodsare required, including the use of domain-specific knowledge forreducing search space, dealing with uncertainty, partial truth andimprecision, efficient linear and/or sub-linear scalability,incremental approaches to knowledge discovery, and increased leveland intelligence of interactivity with human experts and decisionmakers Chapters authored by leading researchers in CI in biologyinformatics. Covers highly relevant topics: rational drug design; analysisof microRNAs and their involvement in human diseases. Supplementary material included: program code and relevant datasets correspond to chapters.
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Biomacromolecules

Introduction to Structure, Function and Informatics

Author: C. Stan Tsai

Publisher: John Wiley & Sons

ISBN: 0470080116

Category: Science

Page: 768

View: 8413

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This book provides an integrated treatment of the structure and function of nucleic acids, proteins, and glycans, including thorough coverage of relevant computational biochemistry. The text begins with an introduction to the biomacromolecules, followed by discussion of methods of isolation and purification, physiochemical and biochemical properties, and structural characteristics. The next section of the book deals with sequence analysis, analysis of conformation using spectroscopy, chemical synthesis, and computational approaches. The following chapters discuss biomolecular interactions, enzyme action, gene transmission, signal transduction, and biomacromolecular informatics. The author concludes with presenting the latest findings in genomics, proteomics, glycomics, and biomacromolecular evolution. This text is an invaluable resource for research professionals wishing to move into genomics, proteomics, and glycomics research. It is also useful for students in biochemistry, molecular biology, bioengineering, biotechnology, and bioinformatics.
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The Proteomics Protocols Handbook

Author: John M. Walker

Publisher: Springer Science & Business Media

ISBN: 1588293432

Category: Medical

Page: 988

View: 2613

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Hands-on researchers describe in step-by-step detail a wide range of proven laboratory methods and bioinformatics tools essential for analysis of the proteome. These cutting-edge techniques (73 in all) addresses such important tasks as sample preparation, 2D-PAGE, gel staining, protein expression profiling, identifying protein-protein interactions, and protein chip tehcnology, as well as a range of newly developed methodologies for determing the structure and function of a protein, including novel mass spectrometry and LC-MS techniques, protein array technology, and a variety of structural and functional proteomics techniques needed to determine the function of newly discovered protein sequences.
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Computational Intelligence in Medical Informatics

Author: Arpad Kelemen,Ajith Abraham,Yulan Liang

Publisher: Springer Science & Business Media

ISBN: 3540757678

Category: Medical

Page: 379

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Medical Informatics (MI) is an emerging interdisciplinary science. This book deals with the application of computational intelligence in MI. Addressing the various issues of medical informatics using different computational intelligence approaches is the novelty of this edited volume. This volume comprises of 15 chapters selected on the basis of fundamental ideas/concepts including an introductory chapter giving the fundamental definitions and some important research challenges.
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Handbook of Hidden Markov Models in Bioinformatics

Author: Martin Gollery

Publisher: CRC Press

ISBN: 1420011804

Category: Science

Page: 176

View: 7624

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Demonstrating that many useful resources, such as databases, can benefit most bioinformatics projects, the Handbook of Hidden Markov Models in Bioinformatics focuses on how to choose and use various methods and programs available for hidden Markov models (HMMs). The book begins with discussions on key HMM and related profile methods, including the HMMER package, the sequence analysis method (SAM), and the PSI-BLAST algorithm. It then provides detailed information about various types of publicly available HMM databases, such as Pfam, PANTHER, COG, and metaSHARK. After outlining ways to develop and use an automated bioinformatics workflow, the author describes how to make custom HMM databases using HMMER, SAM, and PSI-BLAST. He also helps you select the right program to speed up searches. The final chapter explores several applications of HMM methods, including predictions of subcellular localization, posttranslational modification, and binding site. By learning how to effectively use the databases and methods presented in this handbook, you will be able to efficiently identify features of biological interest in your data.
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Sequence — Evolution — Function

Computational Approaches in Comparative Genomics

Author: Eugene Koonin,Michael Y. Galperin

Publisher: Springer Science & Business Media

ISBN: 9781402072741

Category: Science

Page: 462

View: 8142

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Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.
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