Overview
Describes and evaluates recent methods for System Genetics data analysis
Critically evaluates various algorithms used to analyze Systems Genetics data
Put together in a community effort by the experts in the field
Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
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Front Matter
Keywords
About this book
This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.
Editors and Affiliations
Bibliographic Information
Book Title: Gene Network Inference
Book Subtitle: Verification of Methods for Systems Genetics Data
Editors: Alberto Fuente
DOI: https://doi.org/10.1007/978-3-642-45161-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-45160-7Published: 15 January 2014
Softcover ISBN: 978-3-662-52204-2Published: 27 August 2016
eBook ISBN: 978-3-642-45161-4Published: 03 January 2014
Edition Number: 1
Number of Pages: XI, 130
Number of Illustrations: 16 b/w illustrations, 33 illustrations in colour
Topics: Systems Biology, Bioinformatics, Systems Biology, Computer Appl. in Life Sciences, Gene Expression