Annual Review of Biomedical Data Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Understanding the genetic basis of complex traits is a longstanding challenge in field genomics. Genome-wide association studies have identified thousands variant-trait associations, but most these variants are located noncoding regions, making link to biological function elusive. While traditional approaches, such as transcriptome-wide (TWAS), advanced our understanding by linking gene expression, they often overlook gene-gene interactions. Here, we review current approaches integrate different molecular data, leveraging machine learning methods identify modules based on coexpression and functional relationships. These integrative PhenoPLIER, combine TWAS drug-induced transcriptional profiles effectively capture biologically meaningful networks. This integration provides context-specific disease processes while highlighting both core peripheral genes. insights pave way for novel therapeutic targets enhance interpretability personalized medicine.

Language: Английский