Huan Zhao

This study uses CRISPRi Perturb-seq to analyze 1,408 autism risk genes in human cortical neurons, identifying 215 genes that cause global transcriptomic dysregulation and uncovering shared transcriptional pathways.

The paper uses Perturb-seq in epidermal organoids to study non-canonical NF-κB signaling's role in keratinocyte differentiation.

The paper identifies dynamic regulatory network hubs in human lineage specification using Perturb-Seq and constructs a deep learning model to predict perturbed TFs in patient transcriptomes.

The paper introduces pertTF, a transformer-based model for predicting genetic perturbation responses, showing improved performance in expression prediction and cell identity shifts across cellular contexts.

This study benchmarks and optimizes Perturb-seq in human pluripotent stem cells, identifying shared regulatory networks during cardiomyocyte differentiation.

The paper uses single-cell CRISPRi screens to show variant-associated enhancers regulate cancer genes in breast cancer, revealing network motifs and subtype-specific functions.