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DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins.
He, Chun; Ye, Xinhai; Yang, Yi; Hu, Liya; Si, Yuxuan; Zhao, Xianxin; Chen, Longfei; Fang, Qi; Wei, Ying; Wu, Fei; Ye, Gongyin.
Afiliación
  • He C; State Key Laboratory of Rice Biology and Breeding & Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Ye X; College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
  • Yang Y; Shanghai Institute for Advanced Study, Zhejiang University, Shanghai, China.
  • Hu L; State Key Laboratory of Rice Biology and Breeding & Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Si Y; College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
  • Zhao X; College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
  • Chen L; State Key Laboratory of Rice Biology and Breeding & Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Fang Q; State Key Laboratory of Rice Biology and Breeding & Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Wei Y; State Key Laboratory of Rice Biology and Breeding & Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Wu F; Department of Computer Science, City University of Hong Kong, Hong Kong, China.
  • Ye G; College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Brief Bioinform ; 24(4)2023 07 20.
Article en En | MEDLINE | ID: mdl-37385595
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Hipersensibilidad Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: China
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Hipersensibilidad Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: China