Nucleic Acids Research Advance Access originally published online on November 28, 2006
Nucleic Acids Research 2007 35(Database issue):D386-D390; doi:10.1093/nar/gkl932
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Nucleic Acids Research, 2007, Vol. 35, Database issue D386-D390
© 2006 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.
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MiST: a microbial signal transduction database
1 Joint Institute for Computational Sciences, The University of Tennessee–Oak Ridge National Laboratory Oak Ridge, TN 37831-6173, USA 2 Graduate School of Genome Science and Technology, The University of Tennessee–Oak Ridge National Laboratory Oak Ridge, TN 37831-6173, USA 3 Center for Bioinformatics and Computational Biology, School of Biology, Georgia Institute of Technology Atlanta, GA 30332-0230, USA
*To whom correspondence should be addressed. Tel: +1 865 974 7687; Fax: +865 576 4368; Email: ulrichle{at}ornl.gov
Received August 15, 2006. Revised October 12, 2006. Accepted October 13, 2006.
Signal transduction pathways control most cellular activities in living cells ranging from regulation of gene expression to fine-tuning enzymatic activity and controlling motile behavior in response to extracellular and intracellular signals. Because of their extreme sequence variability and extensive domain shuffling, signal transduction proteins are difficult to identify, and their current annotation in most leading databases is often incomplete or erroneous. To overcome this problem, we have developed the microbial signal transduction (MiST) database (http://genomics.ornl.gov/mist), a comprehensive library of the signal transduction proteins from completely sequenced bacterial and archaeal genomes. By searching for domain profiles that implicate a particular protein as participating in signal transduction, we have systematically identified 69 270 two- and one-component proteins in 365 bacterial and archaeal genomes. We have designed a user-friendly website to access and browse the predicted signal transduction proteins within various organisms. Further capabilities include gene/protein sequence retrieval, visualized domain architectures, interactive chromosomal views for exploring gene neighborhood, advanced querying options and cross-species comparison. Newly available, complete genomes are loaded into the database each month. MiST is the only comprehensive and up-to-date electronic catalog of the signaling machinery in microbial genomes.
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