Year: 2026
Type: preprint
Abstract: Motivation KSTAR is an algorithm with high flexibility for inferring kinase activity from any phosphoproteomic pipeline. However, in its first instantiation (v0.1) it requires Python programming and lots of memory and computational resources. Hence, we wished to improve speed and accessibility for broader uptake by researchers. Results Here, we provide an updated algorithm that improves speed and memory, without affecting accuracy, along with some new features for increased usability and insight. KSTAR v1.2 has also been integrated into Galaxy for programming-free activity analysis and ProteomeScout for dataset preparation and interactive plotting. Availability and implementation KSTAR is available at https://github.com/NaegleLab/KSTAR or on Galaxy on https://usegalaxy.org/ . KSTAR Network resource assets are managed on Figshare at: https://doi.org/10.6084/m9.figshare.14944305 .
Institution: University of Virginia
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7213463366