CCHMM_PROF is a hidden Markov model that exploits the information contained in multiple sequence alignments (profiles) to predict coiled-coil regions. The new method discriminates coiled-coil sequences with an accuracy of 97% and achieves a true positive rate of 79% with only 1% of false positives. Furthermore, when predicting the location of coiled-coil segments in protein sequences, the method reaches an accuracy of 80% at the residue level and a best per-segment and per-protein efficiency of 81% and 80%, respectively. The results indicate that CCHMM_PROF outperforms all the existing tools and can be adopted for large-scale genome annotation.
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Bioinformatics. 2009 Nov 1;25(21):2757-63. Epub 2009 Sep 10.
CCHMM_PROF: a HMM-based coiled-coil predictor with evolutionary information.
Bartoli L, Fariselli P, Krogh A, Casadio R.