论文标题
COVID-19Base：一个探索与Covid-19的生物医学实体的知识库
COVID-19Base: A knowledgebase to explore biomedical entities related to COVID-19
论文作者
论文摘要
我们正在提出Covid-19base，这是一个知识库，该知识基于基于文献挖掘的Covid-19疾病的生物医学实体。为了开发Covid-19base，我们从公开可用的科学文献和相关公共资源中挖掘信息。我们考虑了七个特定于主题的词典，包括人类基因，人miRNA，人LNCRNA，疾病，蛋白质数据库，药物和药物副作用，都集成了与Covid-19有关的所有科学证据。我们已经通过一种新颖的方法采用了自动文献挖掘和标签系统，以根据自然语言处理，情感分析和深度学习来衡量药物对疾病的有效性。据我们所知，这是第一个专门针对Covid-19的知识基础，它通过文献挖掘整合了如此众多的相关生物医学实体。在Covid-19base中报道的那些鉴定的相互作用将有助于研究界发现研究界发现COVID-19的治疗方法可能的方法。
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.
