SOURCE-LINKED INTELLIGENCE
Harnessing the splicing code for targeted control of gene expression
allenges that have limited progress in the AS field. Building on extensive preliminary data, we will use a multidisciplinary approach that combines chemical, structural, cellular, systems biology and machine learning to characterize mechanisms of splice site selection and identify targets for modulating these mechanisms using tool compounds. The outcomes will define key regulatory sequences, splicing factors and molecular interactions involved, thereby illuminating how the splicing machinery efficiently accommodates, yet also discriminates between, a wide range of splice site sequences. This will enable future applications harnessing splice site selection. Our primary goal is to answer the central question, ‘Is it generally possible to modulate splicing with high specificity using small molecules?’ Success will transform our basic understanding of human gene expression and unleash major opportunities for Pharma to develop new therapeutics. RNA splicing, RNA-protein interactions
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 5000764
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T01:21:06.728Z. This is not the publication date.