Suppr超能文献

COVID-KOP:将新兴的 COVID-19 数据与 ROBOKOP 数据库集成。

COVID-KOP: integrating emerging COVID-19 data with the ROBOKOP database.

机构信息

Department of Computer Science, University of North Carolina at Chapel Hill, USA.

Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, USA.

出版信息

Bioinformatics. 2021 May 1;37(4):586-587. doi: 10.1093/bioinformatics/btaa718.

Abstract

SUMMARY

In response to the COVID-19 pandemic, we established COVID-KOP, a new knowledgebase integrating the existing Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP) biomedical knowledge graph with information from recent biomedical literature on COVID-19 annotated in the CORD-19 collection. COVID-KOP can be used effectively to generate new hypotheses concerning repurposing of known drugs and clinical drug candidates against COVID-19 by establishing respective confirmatory pathways of drug action.

AVAILABILITY AND IMPLEMENTATION

COVID-KOP is freely accessible at https://covidkop.renci.org/. For code and instructions for the original ROBOKOP, see: https://github.com/NCATS-Gamma/robokop.

摘要

摘要

为应对 COVID-19 大流行,我们建立了 COVID-KOP,这是一个新的知识库,将现有的 Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways(ROBOKOP)生物医学知识图谱与 CORD-19 集合中 COVID-19 相关的近期生物医学文献中的信息进行了整合。COVID-KOP 可有效用于通过建立药物作用的相应确认途径,针对 COVID-19 提出重新利用已知药物和临床候选药物的新假说。

可及性和实施情况

COVID-KOP 可在 https://covidkop.renci.org/ 免费访问。有关原始 ROBOKOP 的代码和说明,请访问:https://github.com/NCATS-Gamma/robokop。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/366f/8088325/3c45ad6659cb/btaa718f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验