SANS: high-throughput retrieval of protein sequences allowing 50% mismatches | Zendy

Jouko Koskinen | Zendy; Liisa Holm | Zendy

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SANS: high-throughput retrieval of protein sequences allowing 50% mismatches

Author(s) -

Jouko Koskinen,

Liisa Holm

Publication year - 2012

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/bts417

Subject(s) - computer science , nearest neighbor search , sequence (biology) , filter (signal processing) , genome , annotation , similarity (geometry) , software , structural genomics , sequence alignment , information retrieval , computational biology , data mining , gene , biology , protein structure , genetics , artificial intelligence , peptide sequence , image (mathematics) , computer vision , programming language , biochemistry

The genomic era in molecular biology has brought on a rapidly widening gap between the amount of sequence data and first-hand experimental characterization of proteins. Fortunately, the theory of evolution provides a simple solution: functional and structural information can be transferred between homologous proteins. Sequence similarity searching followed by k-nearest neighbor classification is the most widely used tool to predict the function or structure of anonymous gene products that come out of genome sequencing projects.

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