Hierarchical learning of gastric cancer molecular subtypes by integrating multi‐modal DNA‐level omics data and clinical stratification

Abstract Molecular subtyping of gastric cancer (GC) aims to comprehend its genetic landscape. However, the efficacy of current subtyping methods is hampered by their mixed use of molecular features, a lack of strategy optimization, and the limited availability of public GC datasets. There is a press...

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Detalhes bibliográficos

Principais autores:	Binyu Yang, Siying Liu, Jiemin Xie, Xi Tang, Pan Guan, Yifan Zhu, Xuemei Liu, Yunhui Xiong, Zuli Yang, Weiyao Li, Yonghua Wang, Wen Chen, Qingjiao Li, Li C. Xia
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Wiley 2024-06-01
coleção:	Quantitative Biology
Assuntos:	DNA alterations gastric cancer hierarchical classification molecular subtyping multi‐omics
Acesso em linha:	https://doi.org/10.1002/qub2.45
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