Optimizing amino acid groupings for GPCR classification | Zendy

Matthew N. Davies | Zendy; Andrew Secker | Zendy; Alex A. Freitas | Zendy; Edward Clark | Zendy; Jon Timmis | Zendy; Darren R. Flower | Zendy

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Optimizing amino acid groupings for GPCR classification

Author(s) -

Matthew N. Davies,

Andrew Secker,

Alex A. Freitas,

Edward Clark,

Jon Timmis,

Darren R. Flower

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/btn382

Subject(s) - computer science , context (archaeology) , alphabet , representation (politics) , artificial intelligence , amino acid residue , machine learning , data mining , biology , peptide sequence , biochemistry , paleontology , philosophy , linguistics , politics , political science , gene , law

There is much interest in reducing the complexity inherent in the representation of the 20 standard amino acids within bioinformatics algorithms by developing a so-called reduced alphabet. Although there is no universally applicable residue grouping, there are numerous physiochemical criteria upon which one can base groupings. Local descriptors are a form of alignment-free analysis, the efficiency of which is dependent upon the correct selection of amino acid groupings.

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