Comparative analysis of tissue-specific genes in maize based on machine learning models: CNN performs technically best, LightGBM performs biologically soundest.

Wang, Zijie; Zhu, Yuzhi; Liu, Zhule; Li, Hongfu; Tang, Xinqiang; Jiang, Yi

Wang, Zijie; Zhu, Yuzhi; Liu, Zhule; Li, Hongfu; Tang, Xinqiang; Jiang, Yi.

Afiliação

Wang Z; School of Agriculture, Sun Yat-sen University, Shenzhen, China.
Zhu Y; School of Agriculture, Sun Yat-sen University, Shenzhen, China.
Liu Z; School of Agriculture, Sun Yat-sen University, Shenzhen, China.
Li H; School of Agriculture, Sun Yat-sen University, Shenzhen, China.
Tang X; School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China.
Jiang Y; School of Agriculture, Sun Yat-sen University, Shenzhen, China.

Front Genet ; 14: 1190887, 2023.

Article em En | MEDLINE | ID: mdl-37229198

Palavras-chave

CNN; Lightgbm; SHAP (shapley additive explanation); limma; maize; tissue specific genes

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article