KEA3: Improved kinase enrichment analysis via data integration

Maxim V. Kuleshov, Zhuorui Xie, Alexandra B.K. London, Janice Yang, John Erol Evangelista, Alexander Lachmann, Ingrid Shu, Denis Torre, Avi Ma'Ayan

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Phosphoproteomics and proteomics experiments capture a global snapshot of the cellular signaling network, but these methods do not directly measure kinase state. Kinase Enrichment Analysis 3 (KEA3) is a webserver application that infers overrepresentation of upstream kinases whose putative substrates are in a user-inputted list of proteins. KEA3 can be applied to analyze data from phosphoproteomics and proteomics studies to predict the upstream kinases responsible for observed differential phosphorylations. The KEA3 background database contains measured and predicted kinase-substrate interactions (KSI), kinase-protein interactions (KPI), and interactions supported by co-expression and co-occurrence data. To benchmark the performance of KEA3, we examined whether KEA3 can predict the perturbed kinase from single-kinase perturbation followed by gene expression experiments, and phosphoproteomics data collected from kinase-targeting small molecules. We show that integrating KSIs and KPIs across data sources to produce a composite ranking improves the recovery of the expected kinase. The KEA3 webserver is available at

Original languageEnglish
Pages (from-to)W304-W316
JournalNucleic Acids Research
Issue numberW1
StatePublished - 2 Jul 2021


Dive into the research topics of 'KEA3: Improved kinase enrichment analysis via data integration'. Together they form a unique fingerprint.

Cite this