ArticleNature communications2022
KSTAR: An algorithm to predict patient-specific kinase activities from phosphoproteomic data.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity.Nature structural & molecular biology · 2026Article
- KSTAR v1.2: A faster and more and accessible KSTAR for kinase activity inference.bioRxiv : the preprint server for biology · 2026Article
- Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges.Current medical science · 2026Review
- Identifying ROCK2 as an intervention target for bilirubin encephalopathy.Fundamental research · 2026Article
- Evaluating splicing factor and kinase network crosstalk through global phosphoproteomics.bioRxiv : the preprint server for biology · 2026Article
- KLSD: A Curated Kinase-Ligand Database Mapping Selectivity Landscapes and Polypharmacology.ACS omega · 2026Article
- Critical role of cell competition in gliomagenesis.bioRxiv : the preprint server for biology · 2026Article
- Recent advances in phosphoproteomics based on mass spectrometry and its clinical application prospects.Frontiers in pharmacology · 2026Review
- Informatics at the Frontier of Cancer Research.Cancer research · 2025Review
- Inference of differential kinase interaction networks with KINference.Bioinformatics (Oxford, England) · 2025Article
- Comprehensive evaluation of phosphoproteomic-based kinase activity inference.Nature communications · 2025Article
- ENQUIRE automatically reconstructs, expands, and drives enrichment analysis of gene and Mesh co-occurrence networks from context-specific biomedical literature.PLoS computational biology · 2025Article
- Phosphoproteomics for studying signaling pathways evoked by hormones of the renin-angiotensin system: A source of untapped potential.Acta physiologica (Oxford, England) · 2025Review
- A computational tool to infer enzyme activity using post-translational modification profiling data.Communications biology · 2025Article
- PTMNavigator: interactive visualization of differentially regulated post-translational modifications in cellular signaling pathways.Nature communications · 2025Article
- Identification of Protein Kinase Drug Targets Using Activity Estimation in Clinical Phosphoproteomics.Methods in molecular biology (Clifton, N.J.) · 2025Article
- PhosX: data-driven kinase activity inference from phosphoproteomics experiments.Bioinformatics (Oxford, England) · 2024Article
- Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis.Nature communications · 2024Article
- KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data.iScience · 2024Article
- Functional Impact of Protein-RNA Variation in Clinical Cancer Analyses.Molecular & cellular proteomics : MCP · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Kinase inhibitors as targeted therapies have played an important role in improving cancer outcomes. However, there are still considerable challenges, such as resistance, non-response, patient stratification, polypharmacology, and identifying combination therapy where understanding a tumor kinase activity profile could be transformative. Here, we develop a graph- and statistics-based algorithm, called KSTAR, to convert phosphoproteomic measurements of cells and tissues into a kinase activity score that is generalizable and useful for clinical pipelines, requiring no quantification of the phosphorylation sites. In this work, we demonstrate that KSTAR reliably captures expected kinase activity differences across different tissues and stimulation contexts, allows for the direct comparison of samples from independent experiments, and is robust across a wide range of dataset sizes. Finally, we apply KSTAR to clinical breast cancer phosphoproteomic data and find that there is potential for kinase activity inference from KSTAR to complement the current clinical diagnosis of HER2 status in breast cancer patients.
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