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
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: 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.
Great post! I’m really excited about TMHMM 2.0c and its improvements in predicting transmembrane helices. It’s fascinating how advancements in bioinformatics software can enhance our understanding of protein structures. Looking forward to trying it out in my own research!