MorphoITH: a framework for deconvolving intra-tumor heterogeneity using tissue morphology

Abstract Background Tumor evolution, driven by the emergence of genetically and epigenetically distinct subclones, enables cancers to adapt to selective pressures and become more aggressive, posing a major challenge in oncology. Multi-regional sequencing has been the primary means of studying tumor...

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Bibliografiske detaljer

Principais autores:	Aleksandra Weronika Nielsen, Hafez Eslami Manoochehri, Hua Zhong, Vandana Panwar, Vipul Jarmale, Jay Jasti, Mehrdad Nourani, Dinesh Rakheja, James Brugarolas, Payal Kapur, Satwik Rajaram
Format:	Artigo
Sprog:	Inglês
Udgivet:	BMC 2025-09-01
Serier:	Genome Medicine
Fag:	Deep learning Artificial intelligence Kidney cancer CcRCC Tumor morphology Tumor evolution
Online adgang:	https://doi.org/10.1186/s13073-025-01504-x
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