How to Infer Gene Networks from Expression Profiles

Overview

Journal Mol Syst Biol

Specialty Molecular Biology

Date 2007 Feb 15

PMID 17299415

Citations 285

Authors

Mukesh Bansal

Vincenzo Belcastro

Alberto Ambesi-Impiombato

Diego di Bernardo

Affiliations

Soon will be listed here.

Abstract

Inferring, or 'reverse-engineering', gene networks can be defined as the process of identifying gene interactions from experimental data through computational analysis. Gene expression data from microarrays are typically used for this purpose. Here we compared different reverse-engineering algorithms for which ready-to-use software was available and that had been tested on experimental data sets. We show that reverse-engineering algorithms are indeed able to correctly infer regulatory interactions among genes, at least when one performs perturbation experiments complying with the algorithm requirements. These algorithms are superior to classic clustering algorithms for the purpose of finding regulatory interactions among genes, and, although further improvements are needed, have reached a discreet performance for being practically useful.

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