Overview
- Features state-of-the-art computational applications that are crucial for the study of systems toxicology
- Includes approaches ranging from data management to mathematical modelling
- Gathers key advice and practical information to support readers in their pursuit of advancing toxicological study
Part of the book series: Methods in Pharmacology and Toxicology (MIPT)
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Table of contents (16 protocols)
Keywords
About this book
This detailed volume explores key state-of-the-art computational applications that are crucial in Systems Toxicology. The recent technological developments in experimental biology and multi-omics measurements that enable Systems Biology and Systems Toxicology can only be fully leveraged by the application of a broad range of computational approaches ranging from data management to mathematical modeling. Taking this into account, chapters in this book cover data management and processing, data analysis, biological network building and analysis, as well as the application of computational methods to toxicological assessment.
Written for the Methods in Pharmacology and Toxicology series, Computational Systems Toxicology includes the kind of key practical advice that will aid readers in furthering our knowledge of toxic substances and reactions to them.
Editors and Affiliations
Bibliographic Information
Book Title: Computational Systems Toxicology
Editors: Julia Hoeng, Manuel C. Peitsch
Series Title: Methods in Pharmacology and Toxicology
DOI: https://doi.org/10.1007/978-1-4939-2778-4
Publisher: Humana New York, NY
eBook Packages: Springer Protocols
Copyright Information: Springer Science+Business Media New York 2015
Hardcover ISBN: 978-1-4939-2777-7Published: 14 September 2015
Softcover ISBN: 978-1-4939-5003-4Published: 29 October 2016
eBook ISBN: 978-1-4939-2778-4Published: 10 September 2015
Series ISSN: 1557-2153
Series E-ISSN: 1940-6053
Edition Number: 1
Number of Pages: X, 430
Number of Illustrations: 13 b/w illustrations, 96 illustrations in colour
Topics: Pharmacology/Toxicology, Systems Biology