Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models | Zendy

Simon Rogers | Zendy; Mark Girolami | Zendy; Walter Kölch | Zendy; Katrina M. Waters | Zendy; Tao Liu | Zendy; Brian D. Thrall | Zendy; H Wiley | Zendy

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Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models

Author(s) -

Simon Rogers,

Mark Girolami,

Walter Kölch,

Katrina M. Waters,

Tao Liu,

Brian D. Thrall,

H Wiley

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/btn553

Subject(s) - transcriptome , proteome , computational biology , proteomics , cluster analysis , biology , gene expression , computer science , bioinformatics , gene , genetics , machine learning

Modern transcriptomics and proteomics enable us to survey the expression of RNAs and proteins at large scales. While these data are usually generated and analyzed separately, there is an increasing interest in comparing and co-analyzing transcriptome and proteome expression data. A major open question is whether transcriptome and proteome expression is linked and how it is coordinated.

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