Reference : PredictProtein--an open resource for online prediction of protein structural and func...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/16795
PredictProtein--an open resource for online prediction of protein structural and functional features
English
Yachdav, Guy mailto [> >]
Kloppman [> >]
Kajan [> >]
Hecht [> >]
Goldberg [> >]
Hamp [> >]
Honigschmid [> >]
Schafferhans [> >]
Roos, Manfred [> >]
Bernhofer [> >]
Richter [> >]
Ashkenazy [> >]
Punta [> >]
Schlessinger [> >]
Bromberg [> >]
Schneider, Reinhard mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Vriend [> >]
Sander [> >]
Ben-Tal [> >]
Rost [> >]
5-May-2014
Nucleic Acid Research
42
8
Yes
International
[en] PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists
not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
http://hdl.handle.net/10993/16795
10.1093/nar/gku366

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