Knowledge Graphs for Indication Expansion: An Explainable Target-Disease Prediction Method.

ABSTRACT: Indication expansion aims to find new indications for existing targets in order to accelerate the process of launching a new drug for a disease on the market. The rapid increase in data types and data sources for computational drug discovery has fostered the use of semantic knowledge graphs (KGs) for indication expansion through target centric approaches, or in other words, target repositioning. Previously, we developed a novel method to construct a KG for indication expansion studies, with the aim of finding and justifying alternative indications for a target gene of interest. In contrast to other KGs, ours combines human-curated full-text literature and gene expression data from biomedical databases to encode relationships between genes, diseases, and tissues. Here, we assessed the suita

SUBMITTER: Gurbuz O 

PROVIDER: S-EPMC8963915 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature