Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: zero-inflated Poisson regression models to predict abundance of undetected proteins | Zendy

Lei Nie | Zendy; Gang Wu | Zendy; Fred J. Brockman | Zendy; Weiwen Zhang | Zendy

Open Access

Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: zero-inflated Poisson regression models to predict abundance of undetected proteins

Author(s) -

Lei Nie,

Gang Wu,

Fred J. Brockman,

Weiwen Zhang

Publication year - 2006

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/btl134

Subject(s) - desulfovibrio vulgaris , computational biology , proteomics , biology , poisson distribution , dna microarray , count data , transcriptome , gene expression , gene , genetics , statistics , mathematics , bacteria

Integrated analysis of global scale transcriptomic and proteomic data can provide important insights into the metabolic mechanisms underlying complex biological systems. However, because the relationship between protein abundance and mRNA expression level is complicated by many cellular and physical processes, sophisticated statistical models need to be developed to capture their relationship.

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