Recognition of multiple patterns in unaligned sets of sequences: comparison of kernel clustering method with other methods | Zendy

Alexander Kel | Zendy; Yuri Tikunov | Zendy; Nico Voss | Zendy; Edgar Wingender | Zendy

Open Access

Recognition of multiple patterns in unaligned sets of sequences: comparison of kernel clustering method with other methods

Author(s) -

Alexander Kel,

Yuri Tikunov,

Nico Voss,

Edgar Wingender

Publication year - 2004

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/bth111

Subject(s) - cluster analysis , kernel (algebra) , bin , set (abstract data type) , computer science , similarity (geometry) , kernel method , pattern recognition (psychology) , projection (relational algebra) , mathematics , artificial intelligence , computational biology , biology , algorithm , combinatorics , support vector machine , image (mathematics) , programming language

Transcription factor binding sites often differ significantly in their primary sequence and can hardly be aligned. Often one set of sites can contain several subsets of sequences that follow not just one but several different patterns. There is a need for sensitive methods to reveal multiple patterns in unaligned sets of sequences.

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