Meta-analysis of gene expression data: a predictor-based approach | Zendy

Irit Fishel | Zendy; Alon Kaufman | Zendy; Eytan Ruppin | Zendy

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Meta-analysis of gene expression data: a predictor-based approach

Author(s) -

Irit Fishel,

Alon Kaufman,

Eytan Ruppin

Publication year - 2007

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/btm149

Subject(s) - microarray analysis techniques , robustness (evolution) , computer science , set (abstract data type) , microarray databases , microarray , gene chip analysis , data mining , data set , computational biology , gene , artificial intelligence , biology , gene expression , genetics , programming language

With the increasing availability of cancer microarray data sets there is a growing need for integrative computational methods that evaluate multiple independent microarray data sets investigating a common theme or disorder. Meta-analysis techniques are designed to overcome the low sample size typical to microarray experiments and yield more valid and informative results than each experiment separately.

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