title: Interpreting networks in systems biology.
abstract: Implementation of network systems biology principles offers unparalleled opportunity to synthesize and integrate inherently complex high-throughput data for meaningful interpretation. Nonstochastic network templates constructed from extant knowledge facilitate large data set prioritization and prognostication, identifying context-dependent candidates for follow-up functional validation and interpretation. In conjunction, enrichment and representation assessment refines comprehension of network-associated molecular functions and biological processes. Together, exploiting intrinsic network properties provides a value-added decision-support instrument for data deconvolution in systems biomedicine.
authors.affiliation: Center for Regenerative Medicine, Mayo Clinic, Rochester, Minnesota, USA.
authors.forename: D K
authors.initials: DK
authors.lastname: Arrell
authors.forename: A
authors.initials: A
authors.lastname: Terzic
mesh_terms: D003661:Decision Support Techniques; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D053858:Metabolic Networks and Pathways; D049490:Systems Biology / Q000379:methods*