Benchmarking substrate-based kinase activity inference using phosphoproteomic data | Zendy

Claudia Hernández-Armenta | Zendy; David Ochoa | Zendy; Emanuel Gonçalves | Zendy; Julio Sáez-Rodríguez | Zendy; Pedro Beltrão | Zendy

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Benchmarking substrate-based kinase activity inference using phosphoproteomic data

Author(s) -

Claudia Hernández-Armenta,

David Ochoa,

Emanuel Gonçalves,

Julio Sáez-Rodríguez,

Pedro Beltrão

Publication year - 2017

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/btx082

Subject(s) - computational biology , in silico , inference , kinase , computer science , weighting , wilcoxon signed rank test , biology , data mining , artificial intelligence , statistics , gene , genetics , mathematics , medicine , radiology , mann–whitney u test

Phosphoproteomic experiments are increasingly used to study the changes in signaling occurring across different conditions. It has been proposed that changes in phosphorylation of kinase target sites can be used to infer when a kinase activity is under regulation. However, these approaches have not yet been benchmarked due to a lack of appropriate benchmarking strategies.

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