Semi-supervised network inference using simulated gene expression dynamics.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Apr 1, 2018
Abstract
MOTIVATION: Inferring the structure of gene regulatory networks from high-throughput datasets remains an important and unsolved problem. Current methods are hampered by problems such as noise, low sample size, and incomplete characterizations of regulatory dynamics, leading to networks with missing and anomalous links. Integration of prior network information (e.g. from pathway databases) has the potential to improve reconstructions.