Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server.
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.
Käll
Lukas
L
Center for Genomics and Bioinformatics, Karolinska Institutet, S-17177 Stockholm, Sweden. lukall@u.washington.edu
Krogh
Anders
A
Sonnhammer
Erik L L
EL
D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003593:Cytoplasm / Q000378:metabolism; D020407:Internet; D008565:Membrane Proteins / Q000378:metabolism*; D008958:Models, Molecular; D008962:Models, Theoretical; D011381:Programming Languages; D011487:Protein Conformation; D021382:Protein Sorting Signals / Q000502:physiology*; D017433:Protein Structure, Secondary / Q000502:physiology*; D040901:Proteomics / Q000379:methods; D012984:Software
D008565:Membrane Proteins; D021382:Protein Sorting Signals