Predicting protein phosphorylation from gene expression: top methods from the IMPROVER Species Translation Challenge | Zendy

Adel Dayarian | Zendy; Roberto Romero | Zendy; Zhiming Wang | Zendy; Michael Biehl | Zendy; Erhan Bilal | Zendy; Sahand Hormoz | Zendy; Pablo Meyer | Zendy; Raquel Norel | Zendy; Kahn Rhrissorrakrai | Zendy; Gyan Bhanot | Zendy; Feng Luo | Zendy; Adi L. Tarca | Zendy

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Predicting protein phosphorylation from gene expression: top methods from the IMPROVER Species Translation Challenge

Author(s) -

Adel Dayarian,

Roberto Romero,

Zhiming Wang,

Michael Biehl,

Erhan Bilal,

Sahand Hormoz,

Pablo Meyer,

Raquel Norel,

Kahn Rhrissorrakrai,

Gyan Bhanot,

Feng Luo,

Adi L. Tarca

Publication year - 2014

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/btu490

Subject(s) - kegg , phosphorylation , phosphoprotein , gene , protein phosphorylation , biology , gene expression , computational biology , protein expression , bioinformatics , genetics , gene ontology , protein kinase a

Using gene expression to infer changes in protein phosphorylation levels induced in cells by various stimuli is an outstanding problem. The intra-species protein phosphorylation challenge organized by the IMPROVER consortium provided the framework to identify the best approaches to address this issue.

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