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PASSML: Combining evolutionary inference and protein secondary structure prediction

Liò, P; Goldman, N; Thorne, JL; Jones, DT; (1998) PASSML: Combining evolutionary inference and protein secondary structure prediction. Bioinformatics , 14 (8) 726 - 733. 10.1093/bioinformatics/14.8.726.

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Abstract

Motivation: Evolutionary models of amino acid sequences can be adapted to incorporate structure information; protein structure biologists can use phylogenetic relationships among species to improve prediction accuracy. Results: A computer program called PASSML ('Phylogeny and Secondary Structure using Maximum Likelihood') has been developed to implement an evolutionary model that combines protein secondary structure and amino acid replacement. The model is related to that of Dayhoff and co-workers, but we distinguish eight categories of structural environment: α helix, β sheet, turn and coil, each further classified according to solvent accessibility, i.e. buried or exposed. The model of sequence evolution for each of the eight categories is a Markov process with discrete states in continuous time, and the organization of structure along protein sequences is described by a hidden Markov model. This paper describes the PASSML software and illustrates how it allows both the reconstruction of phylogenies and prediction of secondary structure from aligned amino acid sequences. Availability: PASSML 'ANSI C' source code and the example data sets described here are available at http://ng-dec1.gen.cam.ac.uk/hmm/Passml.html and 'downstream ' Web pages.

Type:Article
Title:PASSML: Combining evolutionary inference and protein secondary structure prediction
DOI:10.1093/bioinformatics/14.8.726
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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