Computational and statistical approaches to genomics /

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作者：edited by Wei Zhang and Ilya Shmulevich.

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ISBN：9781402070235

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简介

简介

At the beginning of the post-sequencing era, biology must now work with the enormous amounts of quantitative data being amassed and must render complex problems in mathematical terms, with all of the computational effort that entails. This phenomenon is perhaps best exemplified by the interdisciplinary scientific activity caused by the advent of high-throughput cDNA microarray technology, which facilitates large-scale surveys of gene expression. Biologists must now work together with engineers, statisticians, computer scientists, and other specialists, in order to attain a holistic understanding of the complex relationship between genes within the genome and uncover genetic function and regulation. Computational and Statistical Genomicsaims to help researchers deal with current genomic challenges. Topics covered include: overviews of the role of supercomputers in genomics research, the existing challenges and directions in image processing for microarray technology, and web-based tools for microarray data analysis; approaches to the global modeling and analysis of gene regulatory networks and transcriptional control, using methods, theories, and tools from signal processing, machine learning, information theory, and control theory; state-of-the-art tools in Boolean function theory, time-frequency analysis, pattern recognition, and unsupervised learning, applied to cancer classification, identification of biologically active sites, and visualization of gene expression data; crucial issues associated with statistical analysis of microarray data, statistics and stochastic analysis of gene expression levels in a single cell, statistically sound design of microarray studies and experiments; and biological and medical implications of genomics research. This book is for any researcher, in academia and industry, in biology, computer science, statistics, or engineering, involved in genomic problems. It could also be used as an advanced level textbook in a course focusing on genomic signals, information processing, or genome biology.

Table Of Contents:
Foreword ix
Preface xi

Microarray Image Analysis and Gene Expression Ratio Statistics 1(22)

Yidong Chen

Edward R. Dougherty

Michael L. Bittner

Paul Meltzer

Jeffery Trent

Statistical Considerations in the Assessment of cDNA Microarray Data Obtained Using Amplification 23(18)

Jing Wang

Kevin R. Coombes

Keith Baggerly

Limei Hu

Stanley R. Hamilton

Wei Zhang

Sources of Variation in Microarray Experiments 41(12)

M. Kathleen Kerr

Edward H. Leiter

Laurent Picard

Gary A. Churchill

Studentizing Microarray Data 53(12)

Keith A. Baggerly

Kevin R. Coombes

Kenneth R. Hess

David N. Stivers

Lynne V. Abruzzo

Wei Zhang

Exploratory Clustering of Gene Expression Profiles of Mutated Yeast Strains 65(14)

Merja Oja

Janne Nikkila

Petri Toronen

Garry Wong

Eero Castren

Samuel Kaski

Selecting Informative Genes for Cancer Classification Using Gene Expression Data 79(14)

Tatsuya Akutsu

Satoru Miyano

Design Issues and Comparison of Methods for Microarray-Based Classification 93(20)

Edward R. Dougherty

Sanju N. Attoor

Analyzing Protein Sequences using Signal Analysis Techniques 113(12)

Karen M. Bloch

Gonzalo R. Arce

Statistics of the Numbers of Transcripts and Protein Sequences Encoded in the Genome 125(48)

Vladimir A. Kuznetsov

Normalized Maximum Likelihood Models for Boolean Regression Used for Prediction and Classification in Genomics 173(24)

Ioan Tabus

Jorma Rissanen

Jaakko Astola

Inference of Genetic Regulatory Networks via Best-Fit Extensions 197(14)

Ilya Shmulevich

Antti Saarinen

Olli Yli-Harja

Jaakko Astola

Regularization and Noise Injection for Improving Genetic Network Models 211(16)

Eugene van Someren

Lodewyk Wessels

Marcel Reinders

Eric Backer

Parallel Computation and Visualization Tools for Codetermination Analysis of Multivariate Gene-Expression Relations 227(14)

Edward B. Suh

Edward R. Dougherty

Seungchan Kim

Michael L. Bittner

Yidong Chen

Daniel E. Russ

Robert L. Martino

Human Glimo Diagnosis from Gene Expression Data 241(16)

Gregory N. Fuller

Kenneth R. Hess

Cristian Mircean

Ioan Tabus

Ilya Shmulevich

Chang Hun Rhee

Kenneth D. Aldape

Janet M. Bruner

Raymond A. Sawaya

Wei Zhang

Application of DNA Microarray Technology to Clinical Biopsies of Breast Cancer 257(20)

Lajos Pusztai

W. Fraser Symmans

Thomas A. Buchholz

Jim Stec

Mark Ayers

Ed Clark

Funda Meric

David Stivers

Kenneth Hess

Alternative Splicing: Genetic Complexity in Cancer 277(22)

Sonya W. Song

Gilbert J. Cote

Chunlei Wu

Wei Zhang

Single-Nucleotide Polymorphisms, DNA Repair, and Cancer 299

Qingyi Wei

Erich M. Sturgis

Margaret R. Spitz

Harvey W. Mohrenweiser

Ilya Shmulevich

Shouming Kong

David Cogdell

Qing Mi

Wei Zhang

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