De novo identification of highly diverged protein repeats by probabilistic consistency | Zendy

A. Biegert | Zendy; Johannes Söding | Zendy

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De novo identification of highly diverged protein repeats by probabilistic consistency

Author(s) -

A. Biegert,

Johannes Söding

Publication year - 2008

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btn039

Subject(s) - probabilistic logic , executable , computational biology , tandem repeat , computer science , sequence alignment , sequence (biology) , multiple sequence alignment , biology , homology (biology) , hidden markov model , genetics , algorithm , genome , peptide sequence , artificial intelligence , gene , operating system

An estimated 25% of all eukaryotic proteins contain repeats, which underlines the importance of duplication for evolving new protein functions. Internal repeats often correspond to structural or functional units in proteins. Methods capable of identifying diverged repeated segments or domains at the sequence level can therefore assist in predicting domain structures, inferring hypotheses about function and mechanism, and investigating the evolution of proteins from smaller fragments.

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