The Condition-Dependent Transcriptional Network in Escherichia coli

Karen Lemmens, Tijl De Bie, Thomas Dhollander, Pieter Monsieurs, Bart De Moor, Julio Collado-Vides, Kristof Engelen, Kathleen Marchal

Research output: Contribution to journalA1: Web of Science-article

Abstract

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 frame work 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 v,,ere predicted.

Original languageEnglish
JournalAnnals of the New York Academy of Sciences
Pages (from-to)29-35
Number of pages7
ISSN0077-8923
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventDREAM2 Conference - New York
Duration: 3-Dec-20074-Dec-2007

Keywords

  • transcriptional modules
  • frequent itemset mining
  • DISTILLER
  • EXPRESSION PROFILES
  • REGULATORY NETWORK
  • DATABASE
  • TOOLS

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