Abstract
When using conventional transmembrane topology and signal peptide predictors, such as TMHMM and SignalP, there is a substantial overlap between these two types of predictions. Applying these methods to five complete proteomes, we found that 30-65% of all predicted signal peptides and 25-35% of all predicted transmembrane topologies overlap. This impairs predictions of 5-10% of the proteome, hence this is an important issue in protein annotation. To address this problem, we previously designed a hidden Markov model, Phobius, that combines transmembrane topology and signal peptide predictions. The method makes an optimal choice between transmembrane segments and signal peptides, and also allows constrained and homology-enriched predictions. We here present a web interface (http://phobius.cgb.ki.se and http://phobius.binf.ku.dk) to access Phobius.
Udgivelsesdato: 2007-Jul
Udgivelsesdato: 2007-Jul
Originalsprog | Engelsk |
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Tidsskrift | Nucleic Acids Research |
Vol/bind | 35 |
Udgave nummer | Web Server issue |
Sider (fra-til) | W429-32 |
ISSN | 0305-1048 |
DOI | |
Status | Udgivet - 2007 |