@article{204441,
  author = {Javed Aman and Audrey Zhu and Martin W{\"u}hr and Stanislav Shvartsman and Mona Singh},
  title = {KINAID: an orthology-based kinase-substrate prediction and analysis tool for phosphoproteomics.},
  abstract = {<p><strong>SUMMARY: </strong>Proteome-wide datasets of phosphorylated peptides, either measured in a condition of interest or in response to perturbations, are increasingly becoming available for model organisms across the evolutionary spectrum. We introduce KINAID (KINase Activity and Inference Dashboard), an interactive and extensible tool written in Dash/Plotly, that predicts kinase-substrate interactions, uncovers and displays kinases whose substrates are enriched amongst phosphorylated peptides, interactively illustrates kinase-substrate interactions, and clusters phosphopeptides targeted by similar kinases. KINAID is the first tool of its kind that can analyze data from not only H. sapiens but also 10 additional model organisms (including M. musculus, D. rerio, D. melanogaster, C. elegans, and S. cerevisiae). We demonstrate KINAID{\textquoteright}s utility by applying it to recently published S. cerevisiae phosphoproteomics data.</p><p><strong>AVAILABILITY AND IMPLEMENTATION: </strong>Webserver at https://kinaid.princeton.edu; open-source python library at https://github.com/Singh-Lab/kinaid; archive at https://doi.org/10.24433/CO.8460107.v1.</p><p><strong>SUPPLEMENTARY INFORMATION: </strong>Available at Bioinformatics online.</p>},
  year = {2025},
  journal = {Bioinformatics (Oxford, England)},
  month = {05/2025},
  issn = {1367-4811},
  doi = {10.1093/bioinformatics/btaf300},
  language = {eng},
}