  We are presenting COVID-19Base, a knowledgebase highlighting the biomedical
entities related to COVID-19 disease based on literature mining. To develop
COVID-19Base, we mine the information from publicly available scientific
literature and related public resources. We considered seven topic-specific
dictionaries, including human genes, human miRNAs, human lncRNAs, diseases,
Protein Databank, drugs, and drug side effects, are integrated to mine all
scientific evidence related to COVID-19. We have employed an automated
literature mining and labeling system through a novel approach to measure the
effectiveness of drugs against diseases based on natural language processing,
sentiment analysis, and deep learning. To the best of our knowledge, this is
the first knowledgebase dedicated to COVID-19, which integrates such large
variety of related biomedical entities through literature mining. Proper
investigation of the mined biomedical entities along with the identified
interactions among those, reported in COVID-19Base, would help the research
community to discover possible ways for the therapeutic treatment of COVID-19.
