论文标题
知识4COVID-19：一种基于语义的方法，用于从各种来源构建相关知识图并分析治疗的毒性
Knowledge4COVID-19: A Semantic-based Approach for Constructing a COVID-19 related Knowledge Graph from Various Sources and Analysing Treatments' Toxicities
论文作者
论文摘要
在本文中，我们提出了知识4covid-19，该框架旨在展示整合不同知识来源的力量，以发现由COVID-19治疗和预先存在的疾病药物之间的药物相互作用引起的不良药物影响。最初，我们专注于使用RDF映射语言对映射规则的声明性定义构建知识4 COVID-19知识图（kg）。由于有关药物治疗的有价值信息，药物 - 药物相互作用和副作用存在于科学数据库（例如药物库）或科学文献（例如Cord-19，Cord-19，Covid-19，Covid-19 Open Research DataSet）中的文本描述中，因此知识4COVID-19框架框架框架构成了自然语言处理。知识4COVID-19框架提取了相关的实体和谓词，这些实体和预测能够对COVID-19处理的细粒度描述以及当这些治疗方法与常见合并症（例如高血压，糖尿病或哮喘）结合使用时可能发生的潜在不良事件。此外，除了KG之外，已经开发了几种用于发现和预测药物相互作用和潜在不利影响的技术，目的是提出更准确的治疗病毒治疗。我们提供遍历KG的服务，并可视化一组药物对治疗结果的影响。知识4COVID-19是2020年4月的泛欧黑客＃EUVSVIRUS的一部分，并通过GitHub存储库公开作为资源（https://github.com/sdm-tib/knowledge4covid-19）和doi （https://zenodo.org/record/4701817#.yh336-8zbol）。
In this paper, we present Knowledge4COVID-19, a framework that aims to showcase the power of integrating disparate sources of knowledge to discover adverse drug effects caused by drug-drug interactions among COVID-19 treatments and pre-existing condition drugs. Initially, we focus on constructing the Knowledge4COVID-19 knowledge graph (KG) from the declarative definition of mapping rules using the RDF Mapping Language. Since valuable information about drug treatments, drug-drug interactions, and side effects is present in textual descriptions in scientific databases (e.g., DrugBank) or in scientific literature (e.g., the CORD-19, the Covid-19 Open Research Dataset), the Knowledge4COVID-19 framework implements Natural Language Processing. The Knowledge4COVID-19 framework extracts relevant entities and predicates that enable the fine-grained description of COVID-19 treatments and the potential adverse events that may occur when these treatments are combined with treatments of common comorbidities, e.g., hypertension, diabetes, or asthma. Moreover, on top of the KG, several techniques for the discovery and prediction of interactions and potential adverse effects of drugs have been developed with the aim of suggesting more accurate treatments for treating the virus. We provide services to traverse the KG and visualize the effects that a group of drugs may have on a treatment outcome. Knowledge4COVID-19 was part of the Pan-European hackathon#EUvsVirus in April 2020 and is publicly available as a resource through a GitHub repository (https://github.com/SDM-TIB/Knowledge4COVID-19) and a DOI (https://zenodo.org/record/4701817#.YH336-8zbol).
