Oliver Chalkley

Fully genetically encoded low-molecular-weight protein tags with defined shapes for direct molecular identification by cryo-electron tomography

This paper introduces genetically encoded protein tags with defined shapes for direct molecular identification by cryo-ET, demonstrating their effectiveness in identifying proteins in situ without disrupting native structures.

Testing theoretical minimal genomes using whole-cell models

The paper tests theoretical minimal genomes for Mycoplasma genitalium using a whole-cell model, finding that simulated minimal gene sets fail to produce dividing cells, highlighting the need for species-specific low essential gene identification.

Understanding metabolic behaviour in whole-cell model output

The paper presents an analysis pipeline using machine learning and network analysis to interpret metabolic reaction fluxes from gene knockouts in a whole-cell model of Mycoplasma genitalium.

The genome design suite: enabling massive in-silico experiments to design genomes.

The paper introduces PyGDS, a Python framework for in-silico genome design that enables large-scale experiments across different computational clusters.

Designing Minimal Genomes Using Whole-Cell Models

The paper presents algorithms for genome design using whole-cell models, discovering smaller minimal genomes for Mycoplasma genitalium than previously known.