Matthew G. Durrant

The paper identifies prokaryotic homologs of the major vault protein that assemble into vault nanocapsules, revealing structural and size variability.

The paper uses a genomic language model to cluster and annotate noncoding sequences in prokaryotic genomes, identifying structured RNAs and their potential functions.

The paper uses large language models to discover a novel family of reverse transcriptases with tandem repeat arrays from metagenomic data.

This study engineers recombinases to improve DNA insertion efficiency and specificity in human cells, achieving 53% integration and 97% genome-wide specificity.

This paper describes the engineering of IS622 bridge recombinases to enable efficient and specific DNA rearrangements in the human genome, including insertion, inversion, and excision of up to 0.93 megabases.

A 40B-parameter DNA model trained on 9.3 trillion tokens scores coding and noncoding variants zero-shot, exposes interpretable sequence features, and writes chromosome-scale sequences.

7B-parameter convolution-attention DNA model with 131 kb context, trained on prokaryotic genomes, performs zero-shot fitness and essentiality prediction and generates Cas loci, transposons, and 650 kb sequences.

The paper demonstrates that IS110 insertion sequences use a structured RNA to direct sequence-specific DNA recombination, enabling modular genome editing.

The paper identifies novel transcripts, eQTLs, and caQTLs in African populations and fine-maps GWAS signals for complex diseases.

This study integrates rare large-effect expression variants into polygenic risk scores, showing improved prediction of complex traits by including these variants in risk assessment.

The paper integrates genetic colocalizations with physiological and pharmacological perturbations to identify causal genes for cardiometabolic diseases.

The paper identifies environmental modulators of genetic risk factors for complex traits by integrating perturbation data with GWAS.

This study shows butyrate induces chromatin accessibility changes in colon cancer cells, linking these changes to GWAS loci and somatic mutations in colorectal cancer.

This study introduces SmORFinder, a tool that improves small protein prediction in microbial genomes by combining pHMMs and deep learning, and identifies many core smORFs of unknown function.

The paper characterizes the dynamic multi-omic molecular response to acute exercise and identifies biomarkers of fitness.

The paper analyzes gene expression and splicing changes in human aging using longitudinal RNA sequencing data from the PIVUS study, finding stability in most genetic regulation but dynamic changes in a subset of genes.