TMHMM 2.0c – Prediction of Transmembrane Helices in Proteins

TMHMM 2.0c

:: 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.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

TMHMM

:: MORE INFORMATION

Citation:

Anders Krogh and Bjorn Larsson, Gunnar von Heijne, and Erik L.L. Sonnhammer:
Predicting Transmembrane Protein Topology with a Hidden Markov Model: Application to Complete Genomes.
J. Mol. Biol. 305:567-580, 2001.

Erik L.L. Sonnhammer, Gunnar von Heijne, and Anders Krogh:
A hidden Markov model for predicting transmembrane helices in protein sequences.
In J. Glasgow et al., eds.: Proc. Sixth Int. Conf. on Intelligent
Systems for Molecular Biology, pages 175-182. AAAI Press, 1998.

HMMTOP 2.9 – Predict Transmembrane Helices and Topology of Proteins

HMMTOP 2.9

:: DESCRIPTION

HMMTOP is an automatic server for predicting transmembrane helices and topology of proteins

::DEVELOPER

Gabor E. Tusnády

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 HMMTOP 

:: MORE INFORMATION

Citation:

G.E Tusnády and I. Simon (2001)
The HMMTOP transmembrane topology prediction server
Bioinformatics 17, 849-850