ArticleNature communications2025
Comprehensive evaluation of phosphoproteomic-based kinase activity inference.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Post-translational modifications in Neuroimmune cells during neuroinflammation: integrated regulatory networks and therapeutic opportunities.Biology direct · 2026Review
- Scalable phosphotyrosine enrichment with SH2 superbinder enables deep profiling of EGF responses.The EMBO journal · 2026Article
- Let the peptides shine: SOX (Sulfonamido-OXine)-labelled peptides for direct kinase and phosphatase monitoring.RSC chemical biology · 2026Review
- Article
- Identifying ROCK2 as an intervention target for bilirubin encephalopathy.Fundamental research · 2026Article
- A 15-layer multi-omics analysis of gastric cancer ecotypes provides therapeutic insights.Cell reports. Medicine · 2026Article
- Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- Multi-layered molecular profiling informs the diagnosis and targeted therapy of desmoplastic small round cell tumor.Nature communications · 2026Article
- Clinical Applications of Phosphoproteomics: Illuminating Cancer Signaling and Enabling Rational Therapeutic Strategies.Cancer science · 2026Review
- Benchmarking EGF signaling pathway inference using phosphoproteomics and kinase-substrate interactions.Nature communications · 2026Article
- Integrated proteomic and phosphoproteomic analysis reveals the MAPK cascade as a key regulator of ethylene-induced latex production in Hevea brasiliensis.Stress biology · 2026Article
- Integrating artificial intelligence across the cancer drug discovery pipeline using a design-test-refine workflow.Frontiers in oncology · 2026Review
- Spatial regulation of AMPK activity under oxidative stress requires LKB1.bioRxiv : the preprint server for biology · 2025Article
- HIV-1 latency reversing agents converge on phosphoregulation of nuclear protein complexes.bioRxiv : the preprint server for biology · 2025Article
- Computational Approaches for Pathway-Centric Analysis of Protein Post-Translational Modifications.Proteomics · 2025Review
- ULMnet: inferring physical cell-cell communication networks from scRNAseq data using univariate linear models.Frontiers in immunology · 2025Article
- PhosX: data-driven kinase activity inference from phosphoproteomics experiments.Bioinformatics (Oxford, England) · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
17 authors.
Funding
Abstract
Kinases regulate cellular processes and are essential for understanding cellular function and disease. To investigate the regulatory state of a kinase, numerous methods have been developed to infer kinase activities from phosphoproteomics data using kinase-substrate libraries. However, few phosphorylation sites can be attributed to an upstream kinase in these libraries, limiting the scope of kinase activity inference. Moreover, inferred activities vary across methods, necessitating evaluation for accurate interpretation. Here, we present benchmarKIN, an R package enabling comprehensive evaluation of kinase activity inference methods. Alongside classical perturbation experiments, benchmarKIN introduces a tumor-based benchmarking approach utilizing multi-omics data to identify highly active or inactive kinases. We used benchmarKIN to evaluate kinase-substrate libraries, inference algorithms and the potential of adding predicted kinase-substrate interactions to overcome the coverage limitations. Our evaluation shows most computational methods perform similarly, but the choice of library impacts the inferred activities with a combination of manually curated libraries demonstrating superior performance in recapitulating kinase activities. Additionally, in the tumor-based evaluation, adding predicted targets from NetworKIN further boosts the performance. We then demonstrate how kinase activity inference aids characterize kinase inhibitor responses in cell lines. Overall, benchmarKIN helps researchers to select reliable methods for identifying deregulated kinases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.