Published on in Vol 8, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21648, first published .
Toward Preparing a Knowledge Base to Explore Potential Drugs and Biomedical Entities Related to COVID-19: Automated Computational Approach

Toward Preparing a Knowledge Base to Explore Potential Drugs and Biomedical Entities Related to COVID-19: Automated Computational Approach

Toward Preparing a Knowledge Base to Explore Potential Drugs and Biomedical Entities Related to COVID-19: Automated Computational Approach

Journals

  1. Alam T, Lipovich L. miRCOVID-19: Potential Targets of Human miRNAs in SARS-CoV-2 for RNA-Based Drug Discovery. Non-Coding RNA 2021;7(1):18 View
  2. Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. Journal of the American Medical Informatics Association 2021;28(9):2050 View
  3. Supianto A, Nurdiansyah R, Weng C, Zilvan V, Yuwana R, Arisal A, Pardede H, Lee M, Huang C, Ng K. Cluster-based text mining for extracting drug candidates for the prevention of COVID-19 from the biomedical literature. Journal of Taibah University Medical Sciences 2023;18(4):787 View
  4. Basit S, Qureshi R, Musleh S, Guler R, Rahman M, Biswas K, Alam T. COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19. Frontiers in Public Health 2023;11 View
  5. Qureshi R, Irfan M, Gondal T, Khan S, Wu J, Hadi M, Heymach J, Le X, Yan H, Alam T. AI in drug discovery and its clinical relevance. Heliyon 2023;9(7):e17575 View