TIGRESS: Trustful Inference of Gene REgulation using Stability Selection
Inferring the structure of gene regulatory networks (GRN) from a collection of gene expression data has many potential applications, from the elucidation of complex biological processes to the identification of potential drug targets. It is however a notoriously difficult problem, for which the many existing methods reach limited accuracy.
stability selection gene expression data gene regulatory network inference feature selection lars