Target repositioning using multi-layer networks and machine learning: The case of prostate cancer.

ABSTRACT: The discovery of novel therapeutic targets, defined as proteins which drugs can interact with to induce therapeutic benefits, typically represent the first and most important step of drug discovery. One solution for target discovery is target repositioning, a strategy which relies on the repurposing of known targets for new diseases, leading to new treatments, less side effects and potential drug synergies. Biological networks have emerged as powerful tools for integrating heterogeneous data and facilitating the prediction of biological or therapeutic properties. Consequently, they are widely employed to predict new therapeutic targets by characterizing potential candidates, often based on their interactions within a Protein-Protein Interaction (PPI) network, and their proximity to genes a

SUBMITTER: Picard M 

PROVIDER: S-EPMC11231507 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature