Machine learning model on multi-omics data enables risk stratification and identifies molecular heterogeneity and therapeutic targets in glioblastoma
基于多组学数据的机器学习模型能够对胶质母细胞瘤进行风险分层，并识别分子异质性和治疗靶点。
期刊:Molecular Cancer
影响因子:33.9
doi:10.1186/s12943-026-02637-2
Zhang, Zhenyu; Wang, Zilong; Li, Ran; Pei, Dongling; Liu, Jingdian; Qiu, Yuning; Liu, Zaoqu; Wang, Minkai; Ma, Zeyu; Duan, Wenchao; Wang, Weiwei; Yan, Jing; Guo, Yang; Liu, Haoran; Li, Wenyuan; Yu, Yinhui; Chen, Te; Ma, Caoyuan; Yu, Miaomiao; Fu, Jing; Su, Dingyuan; Li, Sen; Geng, Haotian; Yu, Bin; Zhen, Yingwei; Chen, Ruokun; Sun, Qiuchang; Zhao, Yuanshen; Duan, Jingxian; Zheng, Hairong; Liang, Dong; Liu, Xianzhi; Li, Zhi-Cheng; Ji, Yuchen; Yan, Dongming
