Rank order metrics for quantifying the association of sequence features with gene regulation | Zendy

Neil D. Clarke | Zendy; Joshua A. Granek | Zendy

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Rank order metrics for quantifying the association of sequence features with gene regulation

Author(s) -

Neil D. Clarke,

Joshua A. Granek

Publication year - 2003

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/19.2.212

Subject(s) - sequence (biology) , rank (graph theory) , association (psychology) , computational biology , order (exchange) , gene , computer science , genetics , biology , mathematics , combinatorics , psychology , economics , finance , psychotherapist

Genome sequences and transcriptome analyses allow the correlation between gene regulation and DNA sequence features to be studied at the whole-genome level. To quantify these correlations, metrics are needed that can be applied to any sequence feature, regardless of its statistical distribution. It is also desirable for the metric values to be determined objectively, that is, without the use of subjective threshold values.

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