Nucleic Acids Research, 2007, Vol. 35, Web Server issue W353 Currently the Web Server does not support uploading of custom tRNA classiﬁcation models or the exclusion of certain positions from scoring such as the anticodon. However, these functionalities are available in the standalone version which is available free for download and obtainable through http://tfam.lcb.uu.se TFAM results should not be used blindly. We emphasize that TFAM classiﬁcations are statistical and depend on the quality of trusted classiﬁcations that are used to make the models. Diﬀerent models and even diﬀerent ‘tfams’ for diﬀerent functional classes vary in their statistical power and generality. We have provided a guide to the intended use of every component of every model available at the TFAM Web Server, and we also refer to earlier provided statistical results (4). To brieﬂy summarize here, TFAM is not strong at distinguishing alanine and valine tRNAs in bacteria. The selenocysteine model is not very general and can fail to recognize true Sel-Cys tRNAs, nonetheless, the model is useful to distinguish falsely predicted Sel-Cys tRNAs such as called by tRNAscan-SE for ﬁrmicutes with an altered genetic code (data not shown). The kIle model is proteobacterial and does not score well for kIle tRNAs from Cyanobacteria, Bacteroidetes, Aquiﬁciae, Actinobacteria, Chlamydia/Verrucomicrobia group, Planctomycetes or Thermotogae [data not shown, but see also (3)]. This is probably because the determinants for this class are divergent in bacteria, the subject of our current research. Finally, the eukaryotic and archaeal TFAM 0.1 models are provided only for the purpose of initiator tRNA identiﬁcation. We plan major reﬁnements and expansions of the TFAM models, including specializing them to more narrow phyla, towards the goal of general models that nonetheless accurately represent the actual constellation of identity determinants and antideterminants that func- tion together in the context of a speciﬁc translational system. In the meantime, we believe that the model quality and ease of use of the TFAM 1. 0 Web Server can promote practical improvements in the annotation of tRNA genes in genome projects and encourage computational biologi- cal research in tRNA structure, function and evolution already today. SUPPLEMENTARY DATA Supplementary Data are available at NAR Online. ACKNOWLEDGMENTS We thank Paul Higgs and Philippe Boisvert for supplying an initial and unpublished version of a classiﬁcation of the CAU-anticodon-containing tRNAs in proteobacteria, Casey Bergman for verifying the eukaryotic model for Drosophila initiator tRNAs, Emil Lundberg for system administration and support, Erik Bongcam-Rudloﬀ and Apple, Inc. for hardware support and the Linnaeus Centre for Bioinformatics for ﬁnancial support. Funding to pay the Open Access publication charges for this article was provided by the Linnaeus Centre for Bioinformatics. Conﬂict of interest statement. None declared. REFERENCES 1. Lowe,T.M. and Eddy,S.R. (1997) tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res., 25, 955–964. 2. Laslett,D. and Canback,B. (2004) ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res., 32, 11–16. 3. Silva,F.J., Belda,E. and Talens,S.E. 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