CCHMMPROF – Predictor of Coiled-Coils Regions in Proteins Exploiting Evolutionary Information

CCHMMPROF

:: DESCRIPTION

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.

::DEVELOPER

Bologna Biocomputing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Python

:: DOWNLOAD

 CCHMMPROF

:: MORE INFORMATION

Citation

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.

CCHMM – Predictor of Coiled-Coils Regions in Proteins

CCHMM

:: DESCRIPTION

CCHMM (Coiled-Coil Domains with Hidden Markov Models) is a predictor of coiled-coil segments in proteins. The software bases on hidden Markov models that complement the existing methods and outperforms them in the task of locating structurally-defined coiled-coil segments.

::DEVELOPER

Bologna Biocomputing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 No, Only Web Service

:: MORE INFORMATION

Citation

Prediction of Structurally-Determined Coiled-Coil Domains with Hidden Markov Models
Piero Fariselli, Daniele Molinini, Rita Casadio and Anders Krogh
Lecture Notes in Computer Science, 2007, Volume 4414, Bioinformatics Research and Development, Pages 292-302