A new representation for protein secondary structure prediction based on frequent patterns | Zendy

Fabian Birzele | Zendy; Stefan Krämer | Zendy

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A new representation for protein secondary structure prediction based on frequent patterns

Author(s) -

Fabian Birzele,

Stefan Krämer

Publication year - 2006

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/btl453

Subject(s) - support vector machine , computer science , representation (politics) , classifier (uml) , pattern recognition (psychology) , protein secondary structure , artificial intelligence , sequence (biology) , set (abstract data type) , simple (philosophy) , data mining , machine learning , biology , biochemistry , philosophy , genetics , epistemology , politics , political science , law , programming language

A new representation for protein secondary structure prediction based on frequent amino acid patterns is described and evaluated. We discuss in detail how to identify frequent patterns in a protein sequence database using a level-wise search technique, how to define a set of features from those patterns and how to use those features in the prediction of the secondary structure of a protein sequence using support vector machines (SVMs).

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