Spatial multi-omics and AI for decoding tumor heterogeneity: implications for target discovery and therapy resistance.

Raheem K, Yakasiri SS, Guda C

DOI: 10.1016/j.neo.2026.101385
Published: 2026 Oct 24
Container: Neoplasia (New York, N.Y.)
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1016/j.neo.2026.101385,
  title = {Spatial multi-omics and AI for decoding tumor heterogeneity: implications for target discovery and therapy resistance.},
  author = {Raheem K and Yakasiri SS and Guda C},
  year = {2026},
  journal = {Neoplasia (New York, N.Y.)},
  doi = {10.1016/j.neo.2026.101385},
  url = {https://doi.org/10.1016/j.neo.2026.101385}
}

RIS

TY  - JOUR
TI  - Spatial multi-omics and AI for decoding tumor heterogeneity: implications for target discovery and therapy resistance.
AU  - Raheem K
AU  - Yakasiri SS
AU  - Guda C
PY  - 2026
JO  - Neoplasia (New York, N.Y.)
DO  - 10.1016/j.neo.2026.101385
UR  - https://doi.org/10.1016/j.neo.2026.101385
ER  -

APA

K, R., SS, Y., & C, G. (2026). Spatial multi-omics and AI for decoding tumor heterogeneity: implications for target discovery and therapy resistance.. Neoplasia (New York, N.Y.). https://doi.org/10.1016/j.neo.2026.101385

Source records

pubmed · retrieved 2026-11-10T12:27:26.411Z