Discovery of regulatory interactions through perturbation: inference and experimental design

T E Ideker, V Thorsson, R M Karp
2000 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
We present two methods to be used interactively to infer a genetic network from gene expression measurements. The predictor method determines the set of Boolean networks consistent with an observed set of steady-state gene expression profiles, each generated from a different perturbation to the genetic network. The chooser method uses an entropy-based approach to propose an additional perturbation experiment to discriminate among the set of hypothetical networks determined by the predictor.
more » ... e methods may be used iteratively and interactively to successively refine the genetic network: at each iteration, the perturbation selected by the chooser is experimentally performed to generate a new gene expression profile, and the predictor is used to derive a refined set of hypothetical gene networks using the cumulative expression data. Performance of the predictor and chooser is evaluated on simulated networks with varying number of genes and number of interactions per gene.
pmid:10902179 fatcat:c6o3cgtv6rfo3dnxqs6togpvv4