Inferring the role of transcription factors in regulatory networks

Background: Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays. Results: We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of E. coli extracted from the literature (1529 nodes and 3802 edges), and we estimate that 30%...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Philippe Veber, Carito Guziolowski, Michel Le Borgne, Ovidiu Radulescu, Anne Siegel
• Keywords: BMCBI 2008, Expression Profiles, Transcriptional Network, Transcriptional Regulatory Networks