SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity | Zendy

Chr̀istophe Magnan | Zendy; Pierre Baldi | Zendy

Open Access

SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity

Author(s) -

Chr̀istophe Magnan,

Pierre Baldi

Publication year - 2014

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/btu352

Subject(s) - similarity (geometry) , sequence (biology) , structural similarity , artificial intelligence , computer science , protein secondary structure , machine learning , data mining , algorithm , pattern recognition (psychology) , biology , image (mathematics) , biochemistry , genetics

Accurately predicting protein secondary structure and relative solvent accessibility is important for the study of protein evolution, structure and function and as a component of protein 3D structure prediction pipelines. Most predictors use a combination of machine learning and profiles, and thus must be retrained and assessed periodically as the number of available protein sequences and structures continues to grow.

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