The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics

Area of Science:

• Biochemistry
• Systems Biology
• Bioinformatics

Background:

• Understanding cellular signaling pathways is crucial for disease research and drug development.
• Kinase activity changes are key indicators of altered cellular circuitry.
• Kinase-Substrate Enrichment Analysis (KSEA) is a method to infer kinase activity from phosphoproteomics data.

Purpose of the Study:

• To develop a user-friendly, web-based application for KSEA.
• To make computational kinase activity analysis accessible to a broader scientific audience.
• To facilitate the interpretation of phosphoproteomics datasets in various biological contexts.

Main Methods:

• Development of a web application implementing the KSEA algorithm.
• Integration of KSEA into an accessible online tool (KSEA App).
• Provision of the tool as an R package (KSEAapp) and open-source code.

Main Results:

• The KSEA App provides a straightforward interface for analyzing kinase activity.
• The tool enables researchers without programming expertise to perform complex phosphoproteomics data analysis.
• Facilitates rapid estimation of kinase activity changes from high-throughput phosphoproteomics data.

Conclusions:

• The KSEA App democratizes kinase activity analysis for the scientific community.
• This tool accelerates the discovery of signaling pathway alterations in disease and drug treatment.
• The application enhances the utility of phosphoproteomics data in biological research.