Graphical Learning and Causal Inference for Drug Repurposing.

ABSTRACT: Gene expression profiles that connect drug perturbations, disease gene expression signatures, and clinical data are important for discovering potential drug repurposing indications. However, the current approach to gene expression reversal has several limitations. First, most methods focus on validating the reversal expression of individual genes. Second, there is a lack of causal approaches for identifying drug repurposing candidates. Third, few methods for passing and summarizing information on a graph have been used for drug repurposing analysis, with classical network propagation and gene set enrichment analysis being the most common. Fourth, there is a lack of graph-valued association analysis, with current approaches using real-valued association analysis one gene at a time to revers

SUBMITTER: Xu T 

PROVIDER: S-EPMC10418581 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature