Integrating stemness and epithelial-mesenchymal transition signatures with machine learning identifies RUNX1 as a therapeutic vulnerability in colorectal cancer

Computers in Biology and Medicine · Published 2026-06-29 · DOI 10.1016/j.compbiomed.2026.111826

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Authors (3)

Shashank Rao Padubidri, Mahender Kumar Singh, Budheswar Dehury

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Year

2026

Citation

Padubidri, S., Singh, M., Dehury, B. (2026). Integrating stemness and epithelial-mesenchymal transition signatures with machine learning identifies RUNX1 as a therapeutic vulnerability in colorectal cancer. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2026.111826

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