Next generation microarray bioinformatics : methods and protocols
著者
書誌事項
Next generation microarray bioinformatics : methods and protocols
（Methods in molecular biology / John M. Walker, series editor, 802）（Springer protocols）
Humana Press, c2012
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing have prompted biologists and biomedical researchers to move away from microarray-based technology to ultra high-throughput, massively parallel genomic sequencing (Next Generation Sequencing, NGS) technology. In Next Generation Microarray Bioinformatics: Methods and Protocols, expert researchers in the field provide techniques to bring together current computational and statistical methods to analyze and interpreting both microarray and NGS data. These methods and techniques include resources for microarray bioinformatics, microarray data analysis, microarray bioinformatics in systems biology, next generation sequencing data analysis, and emerging applications of microarray and next generation sequencing. Written in the highly successful Methods in Molecular Biology (TM) series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory.
Authoritative and practical, Next Generation Microarray Bioinformatics: Methods and Protocols seeks to aid scientists in the further study of this crucially important research into the human DNA.
目次
TABLE OF CONTENTS
PREFACE
LIST OF CONTRIBUTORS
I) Introduction and Resources for Microarray Bioinformatics
1. A Primer on the Current State of Microarray Technologies
Alexander J. Trachtenberg, Robert J. Chang, Azza E. Abdalla, Andrew Fraser, Steven Y. He, Jessica N. Lacy, Chiara Rivas-Morello, Allison Truong, Gary Hardiman, Lucila Ohno-Machado, Fang Liu, Eivind Hovig and Winston Patrick Kuo
2. The KEGG Databases and Tools Facilitating Omics Analysis: Latest Developments Involving Human Diseases and Pharmaceuticals
Masaaki Kotera, Mika Hirakawa, Toshiaki Tokimatsu, Susumu Goto and Minoru Kanehisa
3. Strategies to Explore Functional Genomics Data Sets in NCBI's GEO Database
Stephen E. Wilhite and Tanya Barrett
II) Microarray Data Analysis (Top down approach)
4. Analyzing Cancer Samples with SNP Arrays
Peter Van Loo, Gro Nilsen, Silje H. Nordgard, Hans Kristian Moen Vollan, Anne- Lise Borresen-Dale, Vessela N. Kristensen and Ole Christian Lingjaerde
5. Classification Approaches for Microarray Gene Expression Data Analysis
Leo Wang-Kit Cheung
6. Biclustering of Time Series Microarray Data
Jia Meng and Yufei Huang
7. Using the Bioconductor GeneAnswers Package to Interpret Gene Lists
Gang Feng, Pamela Shaw, Steven T. Rosen, Simon M. Lin and Warren A. Kibbe
8. Analysis of Isoform Expression from Splicing Array using Multiple Comparisons
T. Murlidharan Nair
9. Functional Comparison of Microarray Data across Multiple Platforms Using the Method of Percentage of Overlapping Functions
Zhiguang Li, Joshua C. Kwekel and Tao Chen
10. Performance Comparison of Multiple Microarray Platforms for Gene Expression Profiling
Fang Liu, Winston P. Kuo, Tor-Kristian Jenssen and Eivind Hovig
11. Integrative Approaches for Microarray Data Analysis
Levi Waldron, Hilary A. Coller and Curtis Huttenhower
III) Microarray Bioinformatics in Systems Biology (Bottom up approach)
12. Modelling Gene Regulation Networks using Ordinary Differential Equations
Jiguo Cao, Xin Qi and Hongyu Zhao
13. Non-homogeneous Dynamic Bayesian Networks in Systems Biology
Sophie Lebre, Frank Dondelinger and Dirk Husmeier
14. Inference of Regulatory Networks from Microarray Data with R and the Bioconductor Package qpgraph
Robert Castelo and Alberto Roverato
15. Effective Nonlinear Methods for Inferring Genetic Regulation from Time-series Microarray Gene Expression Data
Junbai Wang and Tianhai Tian
IV) Next Generation Sequencing Data Analysis
16. An Overview of the Analysis of Next Generation Sequencing Data
Andreas Gogol-Doering and Wei Chen
17. How to Analyze Gene Expression using RNA-Sequencing Data
Daniel Ramskoeld, Ersen Kavak and Rickard Sandberg
18. Analyzing ChIP-seq Data: Preprocessing, Normalization, Differential Identification and Binding Pattern Characterization
Cenny Taslim, Kun Huang, Tim Huang and Shili Lin
19. Identifying Differential Histone Modification Sites from ChIP-seq Data
Han Xu and Wing-Kin Sung
20. ChIP-Seq Data Analysis: Identification of Protein-DNA Binding Sites with SISSRs Peak Finder
Leelavati Narlikar and Raja Jothi
21. Using ChIPMotifs for de novo Motif Discovery of OCT4 and ZNF263 based on ChIP-based High-throughput Experiments
Brian A. Kennedy, Xun Lan, Tim H-M. Huang, Peggy J. Farnham and Victor X. Jin
V) Emerging Applications of Microarray and Next Generation Sequencing
22. Hidden Markov Models for Controlling False Discovery Rate in Genome-Wide Association Analysis
Zhi Wei
23. Employing Gene Set Top Scoring Pairs to Identify Deregulated Pathway-Signatures in Dilated Cardiomyopathy from Integrated Microarray Gene Expression Data
Aik Choon Tan
24. JAMIE: A Software Tool for Jointly Analyzing Multiple ChIP-chip Experiments
Hao Wu and Hongkai Ji
25. Epigenetic Analysis: ChIP-chip and ChIP-seq
Matteo Pellegrini and Roberto Ferrari
26. BiNGS!SL-seq: A Bioinformatics Pipeline for the Analysis and Interpretation of Deep Sequencing Genome-wide Synthetic Lethal Screen
Jihye Kim and Aik Choon Tan
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