Integrated multiomics analysis and advanced machine learning techniques to refine molecular subtypes, stratify prognosis, characterize tumor microenvironment, and identify distinct sensitivity patterns to frontline therapies in lung squamous cell carcinoma

Abstract Lung squamous cell carcinoma (LUSC) is characterized by high aggressiveness and significant heterogeneity, currently lacking highly precise individualized treatment options. Leveraging computational methodologies, we integrated multi-omics data from LUSC patients using 10 clustering algorit...

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Xehetasun bibliografikoak

Egile Nagusiak:	Shi Yan, Xu Zhang, Tongying Xu, Xiangyu Wang, Fanglin Tian, Weina Fan, Yuning Zhan, Li Cai, Ying Xing
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	SpringerOpen 2026-01-01
Saila:	Journal of Big Data
Gaiak:	Bioinformatics Immunotherapy Machine learning Multiomics Precision medicine Lung squamous cell carcinoma
Sarrera elektronikoa:	https://doi.org/10.1186/s40537-025-01354-9
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!