Identifying functionally informative evolutionary sequence profiles | Zendy

Nelson Gil | Zendy; András Fiser | Zendy

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Identifying functionally informative evolutionary sequence profiles

Author(s) -

Nelson Gil,

András Fiser

Publication year - 2017

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/btx779

Subject(s) - computer science , source code , sequence (biology) , set (abstract data type) , annotation , computational biology , selection (genetic algorithm) , sequence alignment , data mining , protein sequencing , homogeneous , artificial intelligence , biology , peptide sequence , genetics , programming language , mathematics , combinatorics , gene

Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually.

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