Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server.
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Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server. / Käll, Lukas; Krogh, Anders; Sonnhammer, Erik L L.
In: Nucleic Acids Research, Vol. 35, No. Web Server issue, 2007, p. W429-32.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server.
AU - Käll, Lukas
AU - Krogh, Anders
AU - Sonnhammer, Erik L L
N1 - Keywords: Computational Biology; Computer Simulation; Cytoplasm; Internet; Membrane Proteins; Models, Molecular; Models, Theoretical; Programming Languages; Protein Conformation; Protein Sorting Signals; Protein Structure, Secondary; Proteomics; Software
PY - 2007
Y1 - 2007
N2 - 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
AB - 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
U2 - 10.1093/nar/gkm256
DO - 10.1093/nar/gkm256
M3 - Journal article
C2 - 17483518
VL - 35
SP - W429-32
JO - Nucleic Acids Research
JF - Nucleic Acids Research
SN - 0305-1048
IS - Web Server issue
ER -
ID: 2736997