Joseph Rosenbluh

This study designs AI-generated anti-CRISPR proteins that inhibit CRISPR-Cas13 with high potency and specificity.

The paper determines the structure of tRNA-bound CRISPR-Cas13 and reveals universal HEPN RNase mechanisms for substrate recognition and catalysis.

The paper generates and validates CRISPR-Cas9 knockout hiPSC lines for Betacellulin to study its role in the EGF system and schizophrenia.

This study uses Perturb-seq to analyze pharmacogenomic interactions in gastric cancer, revealing gene-drug relationships and resistance mechanisms.

The paper identifies SRP19 as a vulnerability in cancers with APC loss, showing that reducing SRP19 inhibits proliferation through ER stress.

The paper introduces SAM-DNMT3A, a CRISPR-based method to induce global DNA methylation, and shows it exploits a vulnerability in ER-positive breast cancers.

The paper identifies pathway-specific functional circular RNAs through loss-of-function screens in cancer cell lines, revealing roles in ferroptosis, WNT, and MAPK signaling.

The paper uses pooled CRISPR screens to identify breast cancer risk genes affecting T cell-mediated killing, finding 33 candidates and showing their impact on immune response and patient outcomes.

The paper quantifies splice-site usage variation across species and identifies intronic hexamer sequences as key determinants of splice-site choice through GWAS and experimental validation.

The paper maps chromatin interactions at 139 breast cancer risk signals using Capture Hi-C and identifies candidate target genes and functional mechanisms.

GeNets provides a platform to compare genomic networks using machine learning and allows analysis of genetic and RNA sequencing data.