Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.02.08.527695v1?rss=1
Authors: Benavides, T. L., Bystroff, C.
Abstract:
Motivation: We present HMMSTRTM, a Hidden Markov Model (HMM) that is useful for predicting topology of transmembrane (TM) proteins. HMMSTRTM provides additional prediction categories of TM regions provided by the PDBTM corpus such as transmembrane beta sheets, coils, and reentrant loops. Results: HMMSTRTM is competitive with existing TM protein topology predictors like TMHMM, it correctly predicts at least half the residues in 96% of all transmembrane helices in a cross validation dataset.
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