Bansal M, Belcastro V, Ambesi-Impiombato A, di Bernardo D
摘 要
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 reverseengineering
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