Predicting lung adenocarcinoma disease progression using methylation-correlated blocks and ensemble machine learning classifiers.

Yu, Xin; Yang, Qian; Wang, Dong; Li, Zhaoyang; Chen, Nianhang; Kong, De-Xin

Yu, Xin; Yang, Qian; Wang, Dong; Li, Zhaoyang; Chen, Nianhang; Kong, De-Xin.

Afiliación

Yu X; State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Yang Q; Agricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China.
Wang D; Agricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China.
Li Z; State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Chen N; Agricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China.
Kong DX; Agricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, China.

PeerJ ; 9: e10884, 2021.

Article en En | MEDLINE | ID: mdl-33628643

Palabras clave

Ensemble model; Lung adenocarcinoma; Methylation correlated blocks

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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PeerJ Año: 2021 Tipo del documento: Article País de afiliación: China

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