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Nucleic Acids Research Advance Access originally published online on June 25, 2007
Nucleic Acids Research 2007 35(Web Server issue):W350-W353; doi:10.1093/nar/gkm393
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Nucleic Acids Research, 2007, Vol. 35, No. suppl_2 W350-W353
© 2007 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.

Articles

TFAM 1.0: an online tRNA function classifier

Helena Tåquist, Yuanyuan Cui and David H. Ardell*

Linnaeus Centre for Bioinformatics, Uppsala University, Box 598, SE-751 24 Uppsala, Sweden

*To whom correspondence should be addressed. Tel: +46 18 471 66 94; Fax: +46 18 471 66 98; Email: david.ardell{at}lcb.uu.se.

Received January 31, 2007. Revised April 3, 2007. Accepted May 1, 2007.

We have earlier published an automated statistical classifier of tRNA function called TFAM. Unlike tRNA gene-finders, TFAM uses information from the total sequences of tRNAs and not just their anticodons to predict their function. Therefore TFAM has an advantage in predicting initiator tRNAs, the amino acid charging identity of nonstandard tRNAs such as suppressors, and the former identity of pseudo-tRNAs. In addition, TFAM predictions are robust to sequencing errors and useful for the statistical analysis of tRNA sequence, function and evolution. Earlier versions of TFAM required a complicated installation and running procedure, and only bacterial tRNA identity models were provided. Here we describe a new version of TFAM with both a Web Server interface and simplified standalone installation. New TFAM models are available including a proteobacterial model for the bacterial lysylated isoleucine tRNAs, making it now possible for TFAM to correctly classify all tRNA genes for some bacterial taxa. First-draft eukaryotic and archaeal models are also provided making initiator tRNA prediction easily accessible genes to any researcher or genome sequencing effort. The TFAM Web Server is available at http://tfam.lcb.uu.se


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