Reverse engineering systems models of regulation: discovery, prediction and mechanisms.
Biological systems can now be understood in comprehensive and quantitative detail using systems biology approaches. Putative genome-scale models can be built rapidly based upon biological inventories and strategic system-wide molecular measurements. Current models combine statistical associations, causative abstractions, and known molecular mechanisms to explain and predict quantitative and complex phenotypes. This top-down 'reverse engineering' approach generates useful organism-scale models despite noise and incompleteness in data and knowledge. Here we review and discuss the reverse engineering of biological systems using top-down data-driven approaches, in order to improve discovery, hypothesis generation, and the inference of biological properties.
Institute for Systems Biology, Seattle, WA, United States.
Justin
J
Ashworth
Elisabeth J
EJ
Wurtmann
Nitin S
NS
Baliga
D000818:Animals; D057005:Bioengineering; D053263:Gene Regulatory Networks; D006801:Humans; D008954:Models, Biological; D049490:Systems Biology / Q000379:methods*