Identification Of key prognostic genes in ovarian cancer using WGCNA and LASSO analysis-Reference-Cited by-同舟云学术

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Identification Of key prognostic genes in ovarian cancer using WGCNA and LASSO analysis

Published:2022-06-16 Issue:1 Volume:15 Page:728-744
ISSN:2689-5293
Container-title:All Life
language:en
Short-container-title:All Life

Author:

Yu Zhong¹²,Ouyang Ling¹²

Affiliation:

1. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of China

2. Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Shenyang, People’s Republic of China

Publisher

Informa UK Limited

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Neuroscience

Link

https://www.tandfonline.com/doi/pdf/10.1080/26895293.2022.2087107

Reference42 articles.

1. Identification and validation of tumor environment phenotypes in lung adenocarcinoma by integrative genome-scale analysis

2. Understanding the tumor immune microenvironment (TIME) for effective therapy

3. DRO1, a Gene Down-regulated by Oncogenes, Mediates Growth Inhibition in Colon and Pancreatic Cancer Cells

4. Identification of a family of human F-box proteins

5. Second-generation PLINK: rising to the challenge of larger and richer datasets

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1. 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

2. Construction of the model for predicting prognosis by key genes regulating EGFR-TKI resistance;Frontiers in Genetics;2022-11-25

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