Lexi R. Bounds

FRACTEL improves power and replication in CRISPR screens by analyzing region-level effects and informing experimental design.

X-Cell predicts causal perturbation responses across diverse cellular contexts using a diffusion language model trained on a large CRISPRi Perturb-seq dataset.

ProPer-seq is a cost-effective, barcode-free single-cell perturbation profiling method that enables scalable analysis of synthetic biology perturbations and reveals transcriptional control principles.

This study identifies hundreds of new cis-regulatory element-gene connections in the MHC locus using CRISPR screens and single-cell transcriptomics, revealing cell type-specific regulatory mechanisms.

The paper identifies mechanoenhancers that regulate transcription in response to matrix stiffness and shows their potential for reprogramming cellular responses to mechanical cues.

The paper develops CLEANSER, a model to filter ambient gRNAs in single-cell CRISPR screens, improving gRNA-cell assignment accuracy and differential gene expression analysis.

This paper introduces launch-dCas9, a machine learning framework to predict guide RNA effects in CRISPR epigenome editing, showing high accuracy and improved gRNA selection.

The paper reports 109 non-coding CRISPR screens analyzing 13.3Mb of the genome, identifies CRE-gene links, and provides guidelines and tools for screening non-coding regulatory elements.