HuKSA: A Machine-Learning-Based Framework for Predicting Human Kinome Selectivity and Polypharmacology.

Saeed MU, Choudhury A, Mathur Y, Hassan MI

DOI: 10.1016/j.jmb.2026.170075
Published: 2026 Oct 22
Container: Journal of molecular biology
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.jmb.2026.170075,
  title = {HuKSA: A Machine-Learning-Based Framework for Predicting Human Kinome Selectivity and Polypharmacology.},
  author = {Saeed MU and Choudhury A and Mathur Y and Hassan MI},
  year = {2026},
  journal = {Journal of molecular biology},
  doi = {10.1016/j.jmb.2026.170075},
  url = {https://doi.org/10.1016/j.jmb.2026.170075}
}

RIS

TY  - JOUR
TI  - HuKSA: A Machine-Learning-Based Framework for Predicting Human Kinome Selectivity and Polypharmacology.
AU  - Saeed MU
AU  - Choudhury A
AU  - Mathur Y
AU  - Hassan MI
PY  - 2026
JO  - Journal of molecular biology
DO  - 10.1016/j.jmb.2026.170075
UR  - https://doi.org/10.1016/j.jmb.2026.170075
ER  -

APA

MU, S., A, C., Y, M., & MI, H. (2026). HuKSA: A Machine-Learning-Based Framework for Predicting Human Kinome Selectivity and Polypharmacology.. Journal of molecular biology. https://doi.org/10.1016/j.jmb.2026.170075

Source records

pubmed · retrieved 2026-11-10T11:41:13.510Z