title: Boosting signal-to-noise in complex biology: prior knowledge is power.
abstract: A major difficulty in the analysis of complex biological systems is dealing with the low signal-to-noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal-to-noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.
authors.affiliation: Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA. tideker@ucsd.edu
authors.forename: Trey
authors.initials: T
authors.lastname: Ideker
authors.forename: Janusz
authors.initials: J
authors.lastname: Dutkowski
authors.forename: Leroy
authors.initials: L
authors.lastname: Hood
mesh_terms: D000465:Algorithms; D004194:Disease / Q000235:genetics; D053263:Gene Regulatory Networks; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D011506:Proteins / Q000378:metabolism; D012815:Signal Processing, Computer-Assisted; D015398:Signal Transduction
chemical_list: D011506:Proteins