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PONGO: a web server for multiple predictions of all-alpha transmembrane proteins
BioDec Srl, via Calzavecchio 20/2, I-40033 Casalecchio di Reno (BO), Italy 1 Stockholm Bioinformatics Center, Stockholm University SE-10691 Stockholm, Sweden 2 University College of London Gower Street, WC1E 6BT London, UK 3 Bioinformatics Center, University of Copenhagen Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark 4 Biocomputing Group, University of Bologna via Selmi 3, I-40126, Bologna, Italy
*To whom correspondence should be addressed. Tel: +39 051 2091284; Fax: +39 051 242576; Email: casadio{at}alma.unibo.it
Received February 10, 2006. Revised March 6, 2006. Accepted March 22, 2006.
The annotation efforts of the BIOSAPIENS European Network of Excellence have generated several distributed annotation systems (DAS) with the aim of integrating Bioinformatics resources and annotating metazoan genomes (http://www.biosapiens.info). In this context, the PONGO DAS server (http://pongo.biocomp.unibo.it) provides the annotation on predictive basis for the all-alpha membrane proteins in the human genome, not only through DAS queries, but also directly using a simple web interface. In order to produce a more comprehensive analysis of the sequence at hand, this annotation is carried out with four selected and high scoring predictors: TMHMM2.0, MEMSAT, PRODIV and ENSEMBLE1.0. The stored and pre-computed predictions for the human proteins can be searched and displayed in a graphical view. However the web service allows the prediction of the topology of any kind of putative membrane proteins, regardless of the organism and more importantly with the same sequence profile for a given sequence when required. Here we present a new web server that incorporates the state-of-the-art topology predictors in a single framework, so that putative users can interactively compare and evaluate four predictions simultaneously for a given sequence. Together with the predicted topology, the server also displays a signal peptide prediction determined with SPEP. The PONGO web server is available at http://pongo.biocomp.unibo.it/pongo.
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