Nucleic Acids Research Advance Access originally published online on November 12, 2008
Nucleic Acids Research 2009 37(Database issue):D629-D635; doi:10.1093/nar/gkn853
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Nucleic Acids Research, 2009, Vol. 37, Database issue D629-D635
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article appears in the following Nucleic Acids Research issue: Database issue [View the issue table of contents]
Articles |
EcID. A database for the inference of functional interactions in E. coli
1Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre–CNIO and 2Computer Sciences Department, Universidad Carlos III de Madrid, Spain
*To whom correspondence should be addressed. Tel: +34 91 732 8000 (ext 2179); Fax: +34 91 732 8000; Email: valencia{at}cnio.es
Received August 22, 2008. Revised October 6, 2008. Accepted October 16, 2008.
The EcID database (Escherichia coli Interaction Database) provides a framework for the integration of information on functional interactions extracted from the following sources: EcoCyc (metabolic pathways, protein complexes and regulatory information), KEGG (metabolic pathways), MINT and IntAct (protein interactions). It also includes information on protein complexes from the two E. coli high-throughput pull-down experiments and potential interactions extracted from the literature using the web services associated to the iHOP text-mining system. Additionally, EcID incorporates results of various prediction methods, including two protein interaction prediction methods based on genomic information (Phylogenetic Profiles and Gene Neighbourhoods) and three methods based on the analysis of co-evolution (Mirror Tree, In Silico 2 Hybrid and Context Mirror). EcID associates to each prediction a specifically developed confidence score. The two main features that make EcID different from other systems are the combination of co-evolution-based predictions with the experimental data, and the introduction of E. coli-specific information, such as gene regulation information from EcoCyc. The possibilities offered by the combination of the EcID database information are illustrated with a prediction of potential functions for a group of poorly characterized genes related to yeaG. EcID is available online at http://ecid.bioinfo.cnio.es.