handbook of hidden markov models in bioinformatics chapman hall crc mathematical and computational biology

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Handbook Of Hidden Markov Models In Bioinformatics

Author : Martin Gollery
ISBN : 9781420011807
Genre : Science
File Size : 78. 87 MB
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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.

Gene Expression Studies Using Affymetrix Microarrays

Author : Hinrich Gohlmann
ISBN : 1420065165
Genre : Science
File Size : 49. 67 MB
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The Affymetrix GeneChip® system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data analyses, Gene Expression Studies Using Affymetrix Microarrays tears down the omnipresent language barriers among molecular biology, bioinformatics, and biostatistics by explaining the entire process of a gene expression study from conception to conclusion. Truly Multidisciplinary: Merges Molecular Biology, Bioinformatics, and Biostatistics This authoritative resource covers important technical and statistical pitfalls and problems, helping not only to explain concepts outside the domain of researchers, but to provide additional guidance in their field of expertise. The book also describes technical and statistical methods conceptually with illustrative, full-color examples, enabling those inexperienced with gene expression studies to grasp the basic principles. Gene Expression Studies Using Affymetrix Microarrays provides novices with a detailed, yet focused introductory course and practical user guide. Specialized experts will also find it useful as a translation dictionary to understand other involved disciplines or to get a broader picture of microarray gene expression studies in general. Although focusing on Affymetrix gene expression, this globally relevant guide covers topics that are equally useful for other microarray platforms and other Affymetrix applications.

Introduction To Computational Proteomics

Author : Golan Yona
ISBN : 1584885556
Genre : Mathematics
File Size : 46. 38 MB
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Introduction to Computational Proteomics introduces the field of computational biology through a focused approach that tackles the different steps and problems involved with protein analysis, classification, and meta-organization. The book starts with the analysis of individual entities and works its way through the analysis of more complex entities, from protein families to interactions, cellular pathways, and gene networks. The first part of the book presents methods for identifying the building blocks of the protein space, such as motifs and domains. It also describes algorithms for assessing similarity between proteins based on sequence and structure analysis as well as mathematical models, such as hidden Markov models and support vector machines, that are used to represent protein families and classify new instances. The second part covers methods that investigate higher order structure in the protein space through the application of unsupervised learning algorithms, such as clustering and embedding. The book also explores the broader context of proteins. It discusses methods for analyzing gene expression data, predicting protein-protein interactions, elucidating cellular pathways, and reconstructing gene networks. This book provides a coherent and thorough introduction to proteome analysis. It offers rigorous, formal descriptions, along with detailed algorithmic solutions and models. Each chapter includes problem sets from courses taught by the author at Cornell University and the Technion. Software downloads, data sets, and other material are available at biozon.org

Structural Bioinformatics

Author : F. J. Burkowski
ISBN : STANFORD:36105131640844
Genre : Computers
File Size : 42. 44 MB
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As the field of bioinformatics grows, the progression of topics in the field reflects separate concerns for sequence data and structure data. This book presents key algorithms - some developed within the artificial intelligence community - and their applications to problems in structural biology and drug discovery.

Introduction To Computational Biology

Author : Michael S. Waterman
ISBN : 0412993910
Genre : Mathematics
File Size : 58. 85 MB
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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.

The Ten Most Wanted Solutions In Protein Bioinformatics

Author : Anna Tramontano
ISBN : 9781420035001
Genre : Mathematics
File Size : 73. 65 MB
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Utilizing high speed computational methods to extrapolate to the rest of the protein universe, the knowledge accumulated on a subset of examples, protein bioinformatics seeks to accomplish what was impossible before its invention, namely the assignment of functions or functional hypotheses for all known proteins. The Ten Most Wanted Solutions in Protein Bioinformatics considers the ten most significant problems occupying those looking to identify the biological properties and functional roles of proteins. - Problem One considers the challenge involved with detecting the existence of an evolutionary relationship between proteins. - Two and Three studies the detection of local similarities between protein sequences and analysis in order to determine functional assignment. - Four, Five, and Six look at how the knowledge of the three-dimensional structures of proteins can be experimentally determined or inferred, and then exploited to understand the role of a protein. - Seven and Eight explore how proteins interact with each other and with ligands, both physically and logically. - Nine moves us out of the realm of observation to discuss the possibility of designing completely new proteins tailored to specific tasks. - And lastly, Problem Ten considers ways to modify the functional properties of proteins. After summarizing each problem, the author looks at and evaluates the current approaches being utilized, before going on to consider some potential approaches.

Pattern Discovery In Bioinformatics

Author : Laxmi Parida
ISBN : 1420010735
Genre : Science
File Size : 61. 68 MB
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The computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data. Taking a systematic approach to pattern discovery, the book supplies sound mathematical definitions and efficient algorithms to explain vital information about biological data. It explores various data patterns, including strings, clusters, permutations, topology, partial orders, and boolean expressions. Each of these classes captures a different form of regularity in the data, providing possible answers to a wide range of questions. The book also reviews basic statistics, including probability, information theory, and the central limit theorem. This self-contained book provides a solid foundation in computational methods, enabling the solution of difficult biological questions.

Introduction To Computational Biology

Author : Bernhard Haubold
ISBN : 9783764373870
Genre : Science
File Size : 64. 72 MB
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Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.

Python For Bioinformatics

Author : Jason Kinser
ISBN : 9781449613075
Genre : Computers
File Size : 44. 14 MB
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Bioinformatics is a growing field that attracts researchers from many different backgrounds who are unfamiliar with the algorithms commonly used in the field. Python for Bioinformatics provides a clear introduction to the Python programming language and instructs beginners on the development of simple programming exercises . Ideal for those with some knowledge of computer programming languages, this book emphasizes Python syntax and methodologies. The text is divided into three complete sections; the first provides an explanation of general Python programming, the second includes a detailed discussion of the Python tools typically used in bioinformatics including clustering, associative memories, and mathematical analysis techniques, and the third section demonstrates how these tools are implemented through numerous applications.

Statistical Methods In Bioinformatics

Author : Warren J. Ewens
ISBN : 9781475732474
Genre : Medical
File Size : 70. 62 MB
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There was a real need for a book that introduces statistics and probability as they apply to bioinformatics. This book presents an accessible introduction to elementary probability and statistics and describes the main statistical applications in the field.

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