Extracting insight from noisy cellular networks

Christian R Landry; Emmanuel D Levy; Diala Abd Rabbo; Kirill Tarassov; Stephen W Michnick

doi:10.1016/j.cell.2013.11.003

Extracting insight from noisy cellular networks

Cell. 2013 Nov 21;155(5):983-9. doi: 10.1016/j.cell.2013.11.003.

Authors

Christian R Landry¹, Emmanuel D Levy, Diala Abd Rabbo, Kirill Tarassov, Stephen W Michnick

Affiliation

¹ Département de Biologie, IBIS and PROTEO, Pavillon Charles-Eugene-Marchand, 1030 Avenue de la Medecine, Laval University, Québec City, QC G1V 0A6, Canada.

PMID: 24267884
DOI: 10.1016/j.cell.2013.11.003

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biological Evolution*
Cells / metabolism*
Protein Interaction Maps*
Proteins / chemistry
Proteins / metabolism
Systems Biology / methods*

Substances

Proteins

Abstract

Publication types

MeSH terms

Substances

Grants and funding