Identification of a glioma functional network from gene fitness data using machine learning-Reference-Cited by-同舟云学术

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Identification of a glioma functional network from gene fitness data using machine learning

Published:2022-01-19 Issue:4 Volume:26 Page:1253-1263
ISSN:1582-1838
Container-title:Journal of Cellular and Molecular Medicine
language:en
Short-container-title:J Cellular Molecular Medi

Author:

Xiang Chun‐xiang¹,Liu Xi‐guo²,Zhou Da‐quan³,Zhou Yi³,Wang Xu³,Chen Feng³^ORCID

Affiliation:

1. Department of Pathology Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang, Hubei China

2. Department of Head and Neck Surgery Hubei Cancer Hospital Wuhan, Hubei China

3. Department of Neurosurgery Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang, Hubei China

Publisher

Wiley

Subject

Cell Biology,Molecular Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jcmm.17182

Reference71 articles.

1. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011–2015

2. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary

3. Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071-22072 study): a multicentre, randomised, open-label, phase 3 trial

4. Dose-Dense Temozolomide for Newly Diagnosed Glioblastoma: A Randomized Phase III Clinical Trial

5. A randomised, open label phase III trial with nimotuzumab, an anti-epidermal growth factor receptor monoclonal antibody in the treatment of newly diagnosed adult glioblastoma

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