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Robust Networks discusses general principles behind network models and the essential concepts in mathematical modeling of molecular regulatory networks in biology. This book integrates biological mechanisms using a bottom-up approach in which genes and molecules are organized in complex networks. It relates abstract concepts in combinatorics and graph theory to questions in biology and addresses computational methods for deriving network models from data. It also addresses the testing of inferred networks by perturbation analysis on real biological systems using genomic techniques. With examples from research, this book is ideal for graduate students and researchers in computational biology.
Table of Contents
Introduction. Inferring Networks from Data. Testing Inferred Networks. Small Model Networks. Tractable Network Models. Discussion and Synthesis.