Identifying differentially expressed genes from microarray experiments via statistic synthesis | Zendy

Jean Yang | Zendy; Yuanyuan Xiao | Zendy; Mark R. Segal | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Identifying differentially expressed genes from microarray experiments via statistic synthesis

Author(s) -

Jean Yang,

Yuanyuan Xiao,

Mark R. Segal

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/bti108

Subject(s) - statistic , microarray , computational biology , gene , microarray analysis techniques , microarray databases , biology , computer science , genetics , gene expression , statistics , mathematics

A common objective of microarray experiments is the detection of differential gene expression between samples obtained under different conditions. The task of identifying differentially expressed genes consists of two aspects: ranking and selection. Numerous statistics have been proposed to rank genes in order of evidence for differential expression. However, no one statistic is universally optimal and there is seldom any basis or guidance that can direct toward a particular statistic of choice.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research