title: Extracting insight from noisy cellular networks.
abstract: Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched.
authors.affiliation: Département de Biologie, IBIS and PROTEO, Pavillon Charles-Eugene-Marchand, 1030 Avenue de la Medecine, Laval University, Québec City, QC G1V 0A6, Canada.
authors.forename: Christian R
authors.initials: CR
authors.lastname: Landry
authors.forename: Emmanuel D
authors.initials: ED
authors.lastname: Levy
authors.forename: Diala
authors.initials: D
authors.lastname: Abd Rabbo
authors.forename: Kirill
authors.initials: K
authors.lastname: Tarassov
authors.forename: Stephen W
authors.initials: SW
authors.lastname: Michnick
mesh_terms: D005075:Biological Evolution; D002477:Cells / Q000378:metabolism*; D060066:Protein Interaction Maps; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D049490:Systems Biology / Q000379:methods*
chemical_list: D011506:Proteins