Transfer learning of condition-specific perturbation in gene interactions improves drug response prediction.

ABSTRACT:

Summary

Drug response is conventionally measured at the cell level, often quantified by metrics like IC50. However, to gain a deeper understanding of drug response, cellular outcomes need to be understood in terms of pathway perturbation. This perspective leads us to recognize a challenge posed by the gap between two widely used large-scale databases, LINCS L1000 and GDSC, measuring drug response at different levels-L1000 captures information at the gene expression level, while GDSC operates at the cell line level. Our study aims to bridge this gap by integrating the two databases through transfer learning, focusing on condition-specific perturbations in gene interactions from L1000 to interpret drug response integrating both gene and cell levels in GDSC. This transfer learning str

SUBMITTER: Bang D 

PROVIDER: S-EPMC11256952 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature