ArticleScientific reports2014
PSEA: Kinase-specific prediction and analysis of human phosphorylation substrates.
Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 33 citations in OpenAlex.
- GraphPhos: Predict Protein-Phosphorylation Sites Based on Graph Neural Networks.International journal of molecular sciences · 2025Article
- Positional distribution and conservation of major phosphorylated sites in the human kinome.Frontiers in molecular biosciences · 2025Article
- A web portal for exploring kinase-substrate interactions.NPJ systems biology and applications · 2024Article
- Hepatic kynurenic acid mediates phosphorylation of Nogo-A in the medial prefrontal cortex to regulate chronic stress-induced anxiety-like behaviors in mice.Acta pharmacologica Sinica · 2024Article
- Deep Learning in Phosphoproteomics: Methods and Application in Cancer Drug Discovery.Proteomes · 2023Review
- Robust inference of kinase activity using functional networks.Nature communications · 2021Article
- Computational Phosphorylation Network Reconstruction: An Update on Methods and Resources.Methods in molecular biology (Clifton, N.J.) · 2021Article
- A Curated Resource for Phosphosite-specific Signature Analysis.Molecular & cellular proteomics : MCP · 2019Article
- PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection.Scientific reports · 2017Article
- Cucurbitacin B exerts anti-cancer activities in human multiple myeloma cells in vitro and in vivo by modulating multiple cellular pathways.Oncotarget · 2017Article
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Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein phosphorylation catalysed by kinases plays crucial regulatory roles in intracellular signal transduction. With the increasing number of kinase-specific phosphorylation sites and disease-related phosphorylation substrates that have been identified, the desire to explore the regulatory relationship between protein kinases and disease-related phosphorylation substrates is motivated. In this work, we analysed the kinases' characteristic of all disease-related phosphorylation substrates by using our developed Phosphorylation Set Enrichment Analysis (PSEA) method. We evaluated the efficiency of our method with independent test and concluded that our approach is reliable for identifying kinases responsible for phosphorylated substrates. In addition, we found that Mitogen-activated protein kinase (MAPK) and Glycogen synthase kinase (GSK) families are more associated with abnormal phosphorylation. It can be anticipated that our method might be helpful to identify the mechanism of phosphorylation and the relationship between kinase and phosphorylation related diseases. A user-friendly web interface is now freely available at http://bioinfo.ncu.edu.cn/PKPred_Home.aspx.
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