PONGO: a web server for multiple predictions of all-alpha transmembrane proteins

被引:28
作者
Amico, Mauro
Finelli, Michele
Rossi, Ivan
Zauli, Andrea
Elofsson, Arne
Viklund, Hakan
von Heijne, Gunnar
Jones, David
Krogh, Anders
Fariselli, Piero
Martelli, Pier Luigi
Casadio, Rita
机构
[1] Univ Bologna, Biocomp Grp, I-40126 Bologna, Italy
[2] Univ Copenhagen, Bioinformat Ctr, DK-2100 Copenhagen O, Denmark
[3] UCL, London WC1E 6BT, England
[4] Stockholm Univ, Stockholm Bioinformat Ctr, SE-10691 Stockholm, Sweden
[5] BioDec Srl, I-40033 Casalecchio Di Reno, BO, Italy
关键词
D O I
10.1093/nar/gkl208
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:W169 / W172
页数:4
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