DynaPho: a web platform for inferring the dynamics of time-series phosphoproteomics | Zendy

ChiaLang Hsu | Zendy; Jian-Kai Wang | Zendy; Pei-Chun Lu | Zendy; HsuanCheng Huang | Zendy; HsuehFen Juan | Zendy

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DynaPho: a web platform for inferring the dynamics of time-series phosphoproteomics

Author(s) -

ChiaLang Hsu,

Jian-Kai Wang,

Pei-Chun Lu,

HsuanCheng Huang,

HsuehFen Juan

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/btx443

Subject(s) - phosphoproteomics , bottleneck , computer science , computational biology , systems biology , scale (ratio) , data science , bioinformatics , biology , kinase , protein kinase a , embedded system , protein phosphorylation , microbiology and biotechnology , physics , quantum mechanics

Large-scale phosphoproteomics studies have improved our understanding of dynamic cellular signaling, but the downstream analysis of phosphoproteomics data is still a bottleneck. We develop DynaPho, a useful web-based tool providing comprehensive and in-depth analyses of time-course phosphoproteomics data, making analysis intuitive and accessible to non-bioinformatics experts. The tool currently implements five analytic modules, which reveal the transition of biological pathways, kinase activity, dynamics of interaction networks and the predicted kinase-substrate associations. These features can assist users in translating their larger-scale time-course phosphoproteomics data into valuable biological discoveries.

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