Alexandra Pančíková

The paper identifies cis-acting genetic variants affecting enhancer function in Parkinson's Disease using multi-omics data and develops models to predict their regulatory impact.

SPLONGGET enables comprehensive genotype-phenotype analysis by integrating long-read single-cell genome, transcriptome, and open chromatin profiling in thousands of cells.

This study uses deep learning to design synthetic enhancers that target specific cell types in fruit flies and humans, revealing the enhancer code as optimal TF activator motifs and absence of repressor motifs.