By Björn H. Junker, Falk Schreiber
An creation to organic networks and techniques for his or her analysisAnalysis of organic Networks is the 1st e-book of its sort to supply readers with a complete advent to the structural research of organic networks on the interface of biology and laptop technological know-how. The booklet starts off with a quick review of organic networks and graph theory/graph algorithms and is going directly to discover: international community homes, community centralities, community motifs, community clustering, Petri nets, sign transduction and gene rules networks, protein interplay networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks.Analysis of organic Networks is a self-contained advent to this significant learn subject, assumes no professional wisdom in machine technological know-how or biology, and is available to execs and scholars alike. every one bankruptcy concludes with a precis of details and with routines for readers to check their realizing of the fabric offered. also, an FTP web site with hyperlinks to author-provided information for the ebook is accessible for deeper study.This ebook is acceptable as a source for researchers in machine technological know-how, biology, bioinformatics, complicated biochemistry, and the lifestyles sciences, and in addition serves as a terrific reference textual content for graduate-level classes in bioinformatics and organic learn.
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Additional info for Analysis of Biological Networks (Wiley Series in Bioinformatics)
Hypergraphs can be directed or undirected. 8 A metabolic network where an edge connects more than two elements. This hyperedge is labeled with the name of the enzyme catalyzing the reaction. Hypergraphs are not commonly used in graph theory, and many algorithms developed for graphs cannot be directly applied to hypergraphs. Therefore, such graphs are seldom used to model biological networks. Instead these networks are modeled by bipartite graphs, a structure generally used to represent hypergraphs.
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