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The goal of this Network Inference Challenge is to reverse engineer gene regulatory networks from gene expression datasets. Participants are given four microarray compendia and are challenged to infer the structure of the underlying transcriptional regulatory networks.

Three of the four compendia were obtained from microorganisms, some of which are pathogens of clinical relevance. The fourth compendium is based on an in-silico (i.e., simulated) network. Each compendium consists of hundreds of microarray experiments, which include a wide range of genetic, drug, and environmental perturbations (or in the in-silico network case, simulations thereof). Network predictions will be evaluated on a subset of known interactions for each organism, or on the known network for the in-silico case.

Related publication:

Wisdom of crowds for robust gene network inference.

Daniel Marbach, James C Costello, Robert Küffner, Nicole Vega, Robert J Prill, Diogo M Camacho, Kyle R Allison, The DREAM5 Consortium, Manolis Kellis, James J Collins, & Gustavo Stolovitzky
Nature Methods, 9(8):796-804, 2012.

Link to Nature Methods