Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma

Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma

Most human cancers develop from stem and progenitor cell populations through the sequential accumulation of various genetic and epigenetic alterations. Cancer stem cells have been identified from medulloblastoma (MB), but a comprehensive understanding of MB stemness, including the interactions betwe...

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Bibliographic Details
Main Authors: Hao Lian, Yi‐Peng Han, Yu‐Chao Zhang, Yang Zhao, Shan Yan, Qi‐Feng Li, Bao‐Cheng Wang, Jia‐Jia Wang, Wei Meng, Jian Yang, Qin‐Hua Wang, Wei‐Wei Mao, Jie Ma
Format: Article
Language:English
Published: Wiley 2019-10-01
Series:Molecular Oncology
Subjects:
connectivity map
machine‐learning methods
medulloblastoma
prognostic model
stemness
tumor immune environment
Online Access:https://doi.org/10.1002/1878-0261.12557

Internet

https://doi.org/10.1002/1878-0261.12557

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