An Empirical Bayesian Method for Detecting Differentially Expressed Genes Using EST Data | Zendy

Na You | Zendy; Junmei Liu | Zendy; Chang Xuan Mao | Zendy

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An Empirical Bayesian Method for Detecting Differentially Expressed Genes Using EST Data

Author(s) -

Na You,

Junmei Liu,

Chang Xuan Mao

Publication year - 2008

Publication title -

international journal of plant genomics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.454

H-Index - 30

eISSN - 1687-5370

pISSN - 1687-5389

DOI - 10.1155/2008/817210

Subject(s) - bayesian probability , computer science , expressed sequence tag , gene , computational biology , sequence (biology) , data mining , pattern recognition (psychology) , gene expression , artificial intelligence , biology , genetics

Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.

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