Kevin R. Brown

The paper develops a method to quantify genetic interactions from CRISPR-Cas9 screens and identifies systematic variations in screen data.

The paper constructs a genome-scale genetic interaction network from 4 million double mutants in HAP1 cells, revealing conserved genetic network principles across species and uncovering novel gene functions and cancer dependencies.

This study identifies FEN1 as a driver of glioblastoma stem cell survival and temozolomide resistance, showing FEN1 inhibition can enhance TMZ efficacy in aggressive tumors.

This study identifies functional relationships between TSC22D, WNK, and NRBP gene families in macromolecular crowding sensing and cell volume regulation across metazoans.

The paper introduces scPipeline, a tool for multi-level cellular and functional annotation of scRNA-seq data, validated across diverse datasets.

The paper identifies ACE2 as the only common host dependency for SARS-CoV-2 across multiple cell lines, while other host factors are cell line specific.

The paper introduces FLEX, a pipeline for benchmarking CRISPR screen data, and identifies a dominant mitochondria-associated signal in genome-wide screens.

This study maps genetic interactions in FASN-deficient cells to identify genes involved in lipid uptake and metabolic adaptation.

The paper evaluates CRISPR/Cas9 knockout screens in human cell lines and designs an optimized gRNA library to improve gene knockout efficiency and accuracy.

This study identifies and classifies human cell line essential genes using an optimized CRISPR-Cas9 screen, finding twice to thrice as many essential genes as previous RNAi studies.