Prediction of drug sensitivity based on multi-omics data using deep learning and similarity network fusion approaches.

ABSTRACT: With the rapid development of multi-omics technologies and accumulation of large-scale bio-datasets, many studies have conducted a more comprehensive understanding of human diseases and drug sensitivity from multiple biomolecules, such as DNA, RNA, proteins and metabolites. Using single omics data is difficult to systematically and comprehensively analyze the complex disease pathology and drug pharmacology. The molecularly targeted therapy-based approaches face some challenges, such as insufficient target gene labeling ability, and no clear targets for non-specific chemotherapeutic drugs. Consequently, the integrated analysis of multi-omics data has become a new direction for scientists to explore the mechanism of disease and drug. However, the available drug sensitivity prediction models

SUBMITTER: Liu XY 

PROVIDER: S-EPMC10150883 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature