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All Life Volume 15, 2022 - Issue 1

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Cancer Biology

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

Zhong Yua Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of China;b Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Shenyang, People’s Republic of China

Ling Ouyanga Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of China;b Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Shenyang, People’s Republic of ChinaCorrespondence[email protected]

Pages 728-744 | Received 20 Sep 2021, Accepted 07 Apr 2022, Published online: 16 Jun 2022

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https://doi.org/10.1080/26895293.2022.2087107
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Md. Al Mehedi Hasan, Md. Maniruzzaman & Jungpil Shin. (2023) 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 20:6, pages 3786-3799.
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Jinke Zhuge, Xiuqing Wang, Jingtai Li, Tongyuan Wang, Hongkang Wang, Mingxing Yang, Wen Dong & Yong Gao. (2022) Construction of the model for predicting prognosis by key genes regulating EGFR-TKI resistance. Frontiers in Genetics 13.
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