Margaret S. Cheung

This study investigates how cyanophage CP12 modulates host carbon regulation by remodeling interfaces and buffering redox changes during infection.

The paper determines the near-atomic structure of the P-SSP7 virion and identifies five rotational registers defining modular portal-capsid assembly.

The paper develops a 4D whole-cell model of Prochlorococcus marinus MED4 to show how spatial organization and redox PTMs regulate carbon fixation under light disturbance.

The paper constructs gene regulatory networks for three cyanobacteria, identifies stress-related regulators as high-influence nodes, and highlights their importance for bioproduction engineering.

The paper presents a computational model of the S. cerevisiae INO80 chromatin remodeling complex using integrative methods, revealing the structure and dynamics of key modules and introducing the INTEGRATOR workflow tool.

The paper introduces an LLM-driven pipeline for detecting and structurally modeling post-translational modifications using proteomics data.

This paper identifies conserved transcriptional modules in Prochlorococcus MED4 using RNA-seq data and independent component analysis, revealing core regulatory programs that persist despite extreme genome reduction.

The paper integrates AMGs and phage assembly into a genome-scale metabolic model to predict their impact on host metabolism and phage production, revealing synergistic and antagonistic effects.

This paper develops a scalable and high-quality method for producing marine cyanophage P-SSP7, enabling efficient structural studies and reducing cryo-EM data collection time.

The paper develops and refines methods to sample and sequence cyanobacteria, cyanophages, and their environment in the Salish Sea to study host-pathogen dynamics.

The paper decodes the regulatory architecture of Synechococcus elongatus PCC 7942 under oxidative stress, revealing modular responses that balance growth and defense.

The paper introduces CLEAN-Contact, a contrastive learning framework for enzyme function prediction using amino acid sequences and contact maps, showing improved accuracy over existing methods.