Interpretation of genomic regulatory variation in the human brain and Parkinson’s Disease by integrating deep learning with single-cell multi-omics KU Leuven
The combination of whole-genome sequencing with matching single-cell multi-omics data provides unprecedented opportunities to unravel the impact of genomic variation on gene expression and cell state. In this project, we will use deep learning models and enhancer-based gene regulatory network inference to model enhancers and link them to target genes, applied to human substantia nigra (SN) and cingulate gyrus (CG) brain regions. Next, we will ...