Your browser doesn't support javascript.
loading
Using Machine Learning Methods in Identifying Genes Associated with COVID-19 in Cardiomyocytes and Cardiac Vascular Endothelial Cells.
Xu, Yaochen; Ma, Qinglan; Ren, Jingxin; Chen, Lei; Guo, Wei; Feng, Kaiyan; Zeng, Zhenbing; Huang, Tao; Cai, Yudong.
Afiliación
  • Xu Y; Department of Mathematics, School of Sciences, Shanghai University, Shanghai 200444, China.
  • Ma Q; School of Life Sciences, Shanghai University, Shanghai 200444, China.
  • Ren J; School of Life Sciences, Shanghai University, Shanghai 200444, China.
  • Chen L; College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
  • Guo W; Key Laboratory of Stem Cell Biology, Shanghai Jiao Tong University School of Medicine (SJTUSM) & Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200030, China.
  • Feng K; Department of Computer Science, Guangdong AIB Polytechnic College, Guangzhou 510507, China.
  • Zeng Z; Department of Mathematics, School of Sciences, Shanghai University, Shanghai 200444, China.
  • Huang T; Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Cai Y; CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Life (Basel) ; 13(4)2023 Apr 14.
Article en En | MEDLINE | ID: mdl-37109540
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Life (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Life (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza