Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Background: Quantitative models for transcriptional regulation have shown great promise for advancing our understanding of the biological mechanisms underlying gene regulation. Ho...
Denis C. Bauer, Fabian A. Buske, Timothy L. Bailey
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...