Shiron Drusinsky

This study shows S2F models underestimate causal variant effects, limiting their utility for fine-mapping, but top predictions are reliable.

This paper develops a deep learning model called Performer to predict gene expression from personal genomes, achieving accuracy close to cis-heritability of most genes.

GAME provides a standardized framework for benchmarking genomics models across tasks, enabling consistent evaluation and community contributions.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

This paper develops an automated system to scale patient-derived brain organoids, revealing consistent donor and batch effects and demonstrating reproducible disease phenotypes in tuberous sclerosis models.