Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki.

Affiliation

Ling ZQ; Zhejiang Cancer Research Institute, Zhejiang Province Cancer Hospital, Banshanqiao Guangji Road 38, Hangzhou 310022, China.

Bioinformatics ; 26(11): 1431-6, 2010 Jun 01.

Article in En | MEDLINE | ID: mdl-20400756

Subject(s)

Gene Expression Profiling/methods; Models, Statistical; Biomarkers, Tumor/metabolism; Cell Line, Tumor; Humans; Oligonucleotide Array Sequence Analysis/methods; Reverse Transcriptase Polymerase Chain Reaction

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Models, Statistical / Gene Expression Profiling Type of study: Risk_factors_studies Limits: Humans Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2010 Type: Article Affiliation country: China

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