Evolution-strengthened knowledge graph enables predicting the targetability and druggability of genes.

ABSTRACT: Identifying promising targets is a critical step in modern drug discovery, with causative genes of diseases that are an important source of successful targets. Previous studies have found that the pathogeneses of various diseases are closely related to the evolutionary events of organisms. Accordingly, evolutionary knowledge can facilitate the prediction of causative genes and further accelerate target identification. With the development of modern biotechnology, massive biomedical data have been accumulated, and knowledge graphs (KGs) have emerged as a powerful approach for integrating and utilizing vast amounts of data. In this study, we constructed an evolution-strengthened knowledge graph (ESKG) and validated applications of ESKG in the identification of causative genes. More important

SUBMITTER: Quan Y 

PROVIDER: S-EPMC10178923 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature