Network-based inference from complex proteomic mixtures using SNIPE | Zendy

David P. Nusinow | Zendy; Adam Kieżun | Zendy; Daniel J. O’Connell | Zendy; Joel M. Chick | Zendy; Yingzi Yue | Zendy; Richard L. Maas | Zendy; Steven P. Gygi | Zendy; Shamil Sunyaev | Zendy

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Network-based inference from complex proteomic mixtures using SNIPE

Author(s) -

David P. Nusinow,

Adam Kieżun,

Daniel J. O’Connell,

Joel M. Chick,

Yingzi Yue,

Richard L. Maas,

Steven P. Gygi,

Shamil Sunyaev

Publication year - 2012

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/bts594

Subject(s) - inference , computer science , computational biology , artificial intelligence , biology

Proteomics presents the opportunity to provide novel insights about the global biochemical state of a tissue. However, a significant problem with current methods is that shotgun proteomics has limited success at detecting many low abundance proteins, such as transcription factors from complex mixtures of cells and tissues. The ability to assay for these proteins in the context of the entire proteome would be useful in many areas of experimental biology.

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