Identification of Hepatocellular Carcinoma–Related Genes with a Machine Learning and Network Analysis-Reference-Cited by-同舟云学术

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Identification of Hepatocellular Carcinoma–Related Genes with a Machine Learning and Network Analysis

Published:2015-01 Issue:1 Volume:22 Page:63-71
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Gui Tuantuan¹²,Dong Xiao³⁴,Li Rudong¹,Li Yixue¹³,Wang Zhen¹³

Affiliation:

1. Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P.R. China.

2. University of Chinese Academy of Sciences, Beijing, P.R. China.

3. Shanghai Center for Bioinformation Technology, Shanghai Industrial Technology Institute, Shanghai, P.R. China.

4. Department of Genetics, Albert Einstein College of Medicine, Bronx, New York.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modelling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/cmb.2014.0122

Reference51 articles.

1. Trop-2 overexpression as an independent marker for poor overall survival in ovarian carcinoma patients

2. Molecular Function Prediction Using Neighborhood Features

3. The Polycomb Group Gene Bmi1 Regulates Antioxidant Defenses in Neurons by Repressing p53 Pro-Oxidant Activity

4. Ubiquitin signalling in the NF-κB pathway

5. Metallothioneins in human tumors and potential roles in carcinogenesis

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3. Computational Analysis of Gastric Canceromics Data to Identify Putative Biomarkers;Current Topics in Medicinal Chemistry;2024-01

4. Gene Expression and Metadata Based Identification of Key Genes for Hepatocellular Carcinoma Using Machine Learning and Statistical Models;IEEE/ACM Transactions on Computational Biology and Bioinformatics;2023-11

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