Network Inference in Molecular Biology: A Hands-on Framework

by Jesse M. Lingeman, Dennis Shasha

Overview

Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set.

Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation.

Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.

Product Details

ISBN-13:	9781461431121
Publisher:	Springer New York
Publication date:	05/25/2012
Series:	SpringerBriefs in Electrical and Computer Engineering
Edition description:	2012
Pages:	100
Product dimensions:	6.10(w) x 9.25(h) x 0.09(d)

Table of Contents

The Gene Network Inference Problem.- Experimental Inputs.- Running Examples.- Overall Workflow of Inference.- Sample Pipelines.- Roll Your Own Pipeline.- Appendix.