<p>This volume explores recent techniques for the computational inference of gene regulatory networks (GRNs). The chapters in this book cover topics such as methods to infer GRNs from time-varying data; the extraction of causal information from biological data; GRN inference from multiple heterogene
Gene Regulatory Networks: Methods and Protocols
β Scribed by Juan M. Vaquerizas, Sarah A. Teichmann, Nicholas M. Luscombe (auth.), Bart Deplancke, Nele Gheldof (eds.)
- Publisher
- Humana Press
- Year
- 2012
- Tongue
- English
- Leaves
- 459
- Series
- Methods in Molecular Biology 786
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Gene regulatory networks play a vital role in organismal development and function by controlling gene expression. With the availability of complete genome sequences, several novel experimental and computational approaches have recently been developed which promise to significantly enhance our ability to comprehensively characterize these regulatory networks by enabling the identification of respectively their genomic or regulatory state components, or the interactions between these two in unprecedented detail. Divided into five convenient sections, Gene Regulatory Networks: Methods and Protocols details how each of these approaches contributes to a more thorough understanding of the composition and function of gene regulatory networks, while providing a comprehensive protocol on how to implement them in the laboratory. Written in the highly successful Methods in Molecular Biologyβ’ 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, Gene Regulatory Networks: Methods and Protocols aims to provide novices and experienced researchers alike with a comprehensive and timely toolkit to study gene regulatory networks from the point of data generation to processing, visualization, and modeling.
β¦ Table of Contents
Front Matter....Pages i-xi
Front Matter....Pages 1-1
Front Matter....Pages 3-19
Front Matter....Pages 21-50
Front Matter....Pages 51-63
Front Matter....Pages 65-77
Back Matter....Pages 79-95
....Pages 97-114
β¦ Subjects
Human Genetics; Gene Expression
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