Reconstructing tumor-wise protein expression in tissue microarray studies using a Bayesian cell mixture model | Zendy

Ronglai Shen | Zendy; Jeremy M. G. Taylor | Zendy; Debashis Ghosh | Zendy

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Reconstructing tumor-wise protein expression in tissue microarray studies using a Bayesian cell mixture model

Author(s) -

Ronglai Shen,

Jeremy M. G. Taylor,

Debashis Ghosh

Publication year - 2008

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/btn536

Subject(s) - tissue microarray , bayesian probability , computational biology , expression (computer science) , computer science , protein expression , microarray , artificial intelligence , biology , pattern recognition (psychology) , gene expression , immunohistochemistry , gene , genetics , immunology , programming language

Tissue microarrays (TMAs) quantify tissue-specific protein expression of cancer biomarkers via high-density immuno-histochemical staining assays. Standard analysis approach estimates a sample mean expression in the tumor, ignoring the complex tissue-specific staining patterns observed on tissue arrays.

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