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iCircDA-NEAE: Accelerated attribute network embedding and dynamic convolutional autoencoder for circRNA-disease associations prediction.
Yuan, Lin; Zhao, Jiawang; Shen, Zhen; Zhang, Qinhu; Geng, Yushui; Zheng, Chun-Hou; Huang, De-Shuang.
Affiliation
  • Yuan L; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
  • Zhao J; Shandong Engineering Research Center of Big Data Applied Technology, Faculty of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
  • Shen Z; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China.
  • Zhang Q; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
  • Geng Y; Shandong Engineering Research Center of Big Data Applied Technology, Faculty of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
  • Zheng CH; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China.
  • Huang DS; School of Computer and Software, Nanyang Institute of Technology, Nanyang, China.
PLoS Comput Biol ; 19(8): e1011344, 2023 08.
Article de En | MEDLINE | ID: mdl-37651321

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Algorithmes / ARN circulaire Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: PLoS Comput Biol Sujet du journal: BIOLOGIA / INFORMATICA MEDICA Année: 2023 Type de document: Article Pays d'affiliation: Chine

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Algorithmes / ARN circulaire Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: PLoS Comput Biol Sujet du journal: BIOLOGIA / INFORMATICA MEDICA Année: 2023 Type de document: Article Pays d'affiliation: Chine