The condition-dependent transcriptional network in Escherichia coli

Ann N Y Acad Sci. 2009 Mar;1158:29-35. doi: 10.1111/j.1749-6632.2008.03746.x.


Thanks to the availability of high-throughput omics data, bioinformatics approaches are able to hypothesize thus-far undocumented genetic interactions. However, due to the amount of noise in these data, inferences based on a single data source are often unreliable. A popular approach to overcome this problem is to integrate different data sources. In this study, we describe DISTILLER, a novel framework for data integration that simultaneously analyzes microarray and motif information to find modules that consist of genes that are co-expressed in a subset of conditions, and their corresponding regulators. By applying our method on publicly available data, we evaluated the condition-specific transcriptional network of Escherichia coli. DISTILLER confirmed 62% of 736 interactions described in RegulonDB, and 278 novel interactions were predicted.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Databases, Genetic
  • Escherichia coli / genetics*
  • Gene Expression Profiling
  • Gene Expression Regulation, Bacterial*
  • Gene Regulatory Networks*
  • Models, Genetic
  • Oligonucleotide Array Sequence Analysis