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LPI-CSFFR: Combining serial fusion with feature reuse for predicting LncRNA-protein interactions.
Huang, Xiaoqian; Shi, Yi; Yan, Jing; Qu, Wenyan; Li, Xiaoyi; Tan, Jianjun.
Afiliación
  • Huang X; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China.
  • Shi Y; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China.
  • Yan J; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China.
  • Qu W; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China.
  • Li X; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China.
  • Tan J; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China. Electronic address: tanjianjun@bjut.edu
Comput Biol Chem ; 99: 107718, 2022 Aug.
Article en En | MEDLINE | ID: mdl-35785626

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ARN Largo no Codificante Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: Comput Biol Chem Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA / QUIMICA Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ARN Largo no Codificante Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: Comput Biol Chem Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA / QUIMICA Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido