cDREM: Inferring Dynamic Combinatorial Gene Regulation

Inferring combinatorial regulation of transcription in silico

In this paper, we propose a functional view on the in silico prediction of transcriptional regulation. We present a method to predict biological functions regulated by a combinatorial interaction of transcription factors. Using a rigorous statistic, this approach intersects the presence of transcription factor binding sites in gene upstream sequences with Gene Ontology terms associated with the...

Inferring gene regulation networks

A current challenge in system biology is to infer the regulation network of a family of p genes from a n-sample of microarrays, with n (much) smaller than p. Gaussian graphical models are simple models to describe these regulation networks. We propose a procedure that performs Gaussian graph estimation by model selection. We introduce a collection of candidate graphs and then select one of them...

Inferring Combinatorial Regulation of Binding Sites and Transcription Factors on Gene Expression

Combinatorial Gene Regulation Using Auto-Regulation

As many as 59% of the transcription factors in Escherichia coli regulate the transcription rate of their own genes. This suggests that auto-regulation has one or more important functions. Here, one possible function is studied. Often the transcription rate of an auto-regulator is also controlled by additional transcription factors. In these cases, the way the expression of the auto-regulator re...

Combinatorial gene regulation in Plasmodium falciparum.

The malaria parasite Plasmodium falciparum has a complicated life cycle with large variations in its gene expression pattern, but it contains relatively few specific transcriptional regulators. To elucidate this paradox, we identified regulatory sequences, using an approach that integrates the sequence conservation among species and the correlation in mRNA expression within a species. Our analy...