TMHMM

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Contents


Description

TMHMM -- TransMembrane prediction using Hidden Markov Models -- is a program for predicting transmembrane helices based on a hidden Markov model. It reads a FASTA formatted protein sequence and predicts locations of transmembrane, intracellular and extracellular regions.

Web site

http://www.cbs.dtu.dk/services/TMHMM-2.0/

Example "long" output

# COX2_BACSU Length: 278
# COX2_BACSU Number of predicted TMHs:  3
# COX2_BACSU Exp number of AAs in TMHs: 68.6888999999999
# COX2_BACSU Exp number, first 60 AAs:  39.8875
# COX2_BACSU Total prob of N-in:        0.99950
# COX2_BACSU POSSIBLE N-term signal sequence
COX2_BACSU        TMHMM2.0        inside       1     6
COX2_BACSU        TMHMM2.0        TMhelix      7    29
COX2_BACSU        TMHMM2.0        outside     30    43
COX2_BACSU        TMHMM2.0        TMhelix     44    66
COX2_BACSU        TMHMM2.0        inside      67    86
COX2_BACSU        TMHMM2.0        TMhelix     87   109
COX2_BACSU        TMHMM2.0        outside    110   278 

References

  1. Sonnhammer EL, von Heijne G, and Krogh A. A hidden Markov model for predicting transmembrane helices in protein sequences. Proc Int Conf Intell Syst Mol Biol. 1998;6:175-82. PubMed ID:9783223 | HubMed [tmhmm1998]
  2. Krogh A, Larsson B, von Heijne G, and Sonnhammer EL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001 Jan 19;305(3):567-80. DOI:10.1006/jmbi.2000.4315 | PubMed ID:11152613 | HubMed [tmhmm2001]
  3. Käll L and Sonnhammer EL. Reliability of transmembrane predictions in whole-genome data. FEBS Lett. 2002 Dec 18;532(3):415-8. PubMed ID:12482603 | HubMed [tmhmm2002]
  4. Käll L, Krogh A, and Sonnhammer EL. A combined transmembrane topology and signal peptide prediction method. J Mol Biol. 2004 May 14;338(5):1027-36. DOI:10.1016/j.jmb.2004.03.016 | PubMed ID:15111065 | HubMed [tmhmm2004]
All Medline abstracts: PubMed | HubMed
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