A statistical method for alignment-free comparison of regulatory sequences | Zendy

Miriam Ruth Kantorovitz | Zendy; Gene E. Robinson | Zendy; Saurabh Sinha | Zendy

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A statistical method for alignment-free comparison of regulatory sequences

Author(s) -

Miriam Ruth Kantorovitz,

Gene E. Robinson,

Saurabh Sinha

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm211

Subject(s) - similarity (geometry) , sequence (biology) , multiple sequence alignment , sequence alignment , task (project management) , computer science , pattern recognition (psychology) , f1 score , artificial intelligence , source code , computational biology , mathematics , data mining , biology , genetics , peptide sequence , gene , management , economics , image (mathematics) , operating system

The similarity of two biological sequences has traditionally been assessed within the well-established framework of alignment. Here we focus on the task of identifying functional relationships between cis-regulatory sequences that are non-orthologous or greatly diverged. 'Alignment-free' measures of sequence similarity are required in this regime.

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