Tyler S. Browne

The paper introduces Murmurent, an agentic AI environment that supports biomedical research collaboration by providing infrastructure, specialized agents, memory, traceability, SOP enforcement, and multi-user capacity.

The paper develops PHYCUT, a CRISPR/Cas9 system for multiplex genome editing in the diatom Phaeodactylum tricornutum, demonstrating its use to reduce fucosylation of secreted proteins.

The paper improves deep learning models for predicting sgRNA/Cas9 activity by optimizing data curation and filtering, resulting in better generalization across species and data types.

This study uses machine learning to predict SaCas9 activity in bacteria, revealing that PAM adenine methylation and flanking sequences significantly influence activity.

The paper develops a transfer learning model, crisprHAL, to improve SpCas9/sgRNA activity prediction using small high-quality datasets.

This paper presents a telomere-to-telomere genome assembly of Phaeodactylum tricornutum using Oxford Nanopore long reads, identifying 25 nuclear chromosomes and improving genetic engineering opportunities.

The paper identifies type IV conjugation systems in metagenomic data and shows they differ between age and geographic cohorts, suggesting their use as biomarkers and highlighting limitations of current binning methods.