谷歌浏览器插件
订阅小程序
在清言上使用

GNN-based Biomedical Knowledge Graph Mining in Drug Development

Graph Neural Networks: Foundations, Frontiers, and Applications(2022)

引用 8|浏览3
暂无评分
摘要
Drug discovery and development (D3) is an extremely expensive and time consuming process. It takes tens of years and billions of dollars to make a drug successfully on the market from scratch, which makes this process highly inefficient when facing emergencies such as COVID-19. At the same time, a huge amount of knowledge and experience has been accumulated during the D3 process during the past decades. These knowledge are usually encoded in guidelines or biomedical literature, which provides an important resource containing insights that can be informative of the future D3 process. Knowledge graph (KG) is an effective way of organizing the useful information in those literature so that they can be retrieved efficiently. It also bridges the heterogeneous biomedical concepts that are involved in the D3 process. In this chapter we will review the existing biomedical KG and introduce how GNN techniques can facilitate the D3 process on the KG. We will also introduce two case studies on Parkinson’s disease and COVID-19, and point out future directions. 24.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要