Computational Systems Biology
Humana Press, 01.04.2009 - 587 Seiten
The recent confluence of high throughput methodology for biological data gathering, genome-scale sequencing, and computational processing power has driven a reinvention and expansion of the way we identify, infer, model, and store relationships between molecules, pathways, and cells in living organisms. In Computational Systems Biology, expert investigators contribute chapters which bring together biological data and computational and/or mathematical models of the data to aid researchers striving to create a system that provides both predictive and mechanistic information for a model organism. The volume is organized into five major sections involving network components, network inference, network dynamics, function and evolutionary system biology, and computational infrastructure for systems biology. As a volume of the highly successful Methods in Molecular Biology™ series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results.Comprehensive and up-to-date, Computational Systems Biology serves to motivate and inspire all those who wish to develop a complete description of a biological system.
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StructureBased Ab Initio Prediction of Transcription FactorBinding Sites
Inferring ProteinProtein Interactions from Multiple Protein Domain
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algorithm alignment amino acid analysis approach base pair Bayesian network bicluster binding sites biochemical Bioinformatics Biol biological Bioverse cell cellular cerevisiae clustering algorithms co-expression complex computational conserved correlation Cytoscape data set database decision trees described domain dynamics edges enzyme example expression data expression level expression profiles feedback filter free energy gene expression gene ontology genetic genome graph identify integrated interac interacting proteins interaction networks intron kinetic mapping matrix measure metabolic methods microarray modules molecular molecules motifs mRNA multiple mutations node Nucl organism orthologs parameters pathway positive predicted TRIs protein families protein interactions protein sequences protein-protein interactions query random reaction regulation regulatory networks residues Saccharomyces Saccharomyces cerevisiae samples score SEBINI Section selection signal similar simulation specific Springer Science+Business Media statistical step stochastic structure subset Swiss-Prot Systems Biology Table target tion topology transcription factor TRNs upstream regions variables yeast