Evan T. Geller

A ML-framework for the discovery of next-generation IBD targets using a harmonized single-cell atlas of patient tissue

The paper develops a machine learning framework to identify cell type-specific gene targets for IBD using a harmonized single-cell atlas and validates them experimentally.

Scalable pooled CRISPR screens with single-cell chromatin accessibility profiling

This paper introduces CRISPR-sciATAC, a method linking genetic perturbations to chromatin accessibility in single cells, showing its effectiveness in human and mouse experiments.

Massively parallel discovery of human-specific substitutions that alter neurodevelopmental enhancer activity

The paper identifies human-specific substitutions affecting enhancer activity in neurodevelopmental regions by testing their impact in human neural stem cells.

Massively parallel disruption of enhancers active during human corticogenesis

The paper disrupts enhancers and genes in human neural stem cells to study their effects on proliferation and identifies regulatory elements linked to neurodevelopmental disorders.

A statistical framework for mapping risk genes from de novo mutations in whole-genome sequencing studies

This paper introduces a statistical framework to identify risk genes from de novo mutations in whole-genome sequencing studies, finding new autism risk genes.