Matthew W. Vaughn

This paper introduces DART, a DBTL loop for synthetic genetic circuit design, showing that complex circuits can be more robust and reproducible than simpler ones in budding yeast.

The paper develops a computational method to predict synthetic circuit robustness across growth conditions and validates it with experimental results in budding yeast.

The paper replicates yeast-based logic circuit design assessments using a high-throughput robotic framework, generating more flow cytometry data than the original study.

The paper introduces a machine learning model to predict whole-cell transcriptional responses to combinations of perturbations using data from single inducers.

The paper compares DNA replication timing in mitotic and endocycling cells in maize roots, finding significant shifts in centromere replication timing during the endocycle.

Repliscan classifies replication timing regions from Repli-seq data by normalizing, filtering, and assigning replication signatures, outperforming previous methods with variable thresholds.