Mahfuzur Rahman

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

This study evaluates dimensionality reduction methods to normalize CRISPR screen data and improve functional gene network extraction from the DepMap.

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.