Laurence Yang

Cost adjusted hierarchical defense strategies enables stratified oxidative stress tolerance

This study shows how E. coli uses different oxidative stress tolerance strategies based on stress magnitude, revealing modular defense programs.

StressME: unified computing framework of Escherichia coli metabolism, gene expression, and stress responses

StressME integrates E. coli's metabolic and gene expression responses to thermal, oxidative, and acid stress, revealing cross-stress proteome allocation strategies and trade-offs.

Lab evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance

The paper uses adaptive laboratory evolution and transcriptomic analysis to identify six mechanisms of paraquat tolerance in E. coli.

Novel Context-Specific Genome-Scale Modelling Explores the Potential of Chlamydomonas reinhardtii for Synthetic Biology Applications

The paper develops a pipeline to predict cellular metabolism from gene expression data using genome-scale models, applied to study TAG overproduction in Chlamydomonas reinhardtii.

APRILE: Exploring the Molecular Mechanisms of Drug Side Effects with Explainable Graph Neural Networks

APRILE uses explainable graph neural networks to identify molecular mechanisms of polypharmacy side effects, generating explanations for over 900,000 side effect-drug pairs.

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

The paper uses genome-scale models to compute proteome allocation under different conditions, revealing variability in cofactor use and protein composition for E. coli growth.

Visualizing metabolic network dynamics through time-series metabolomics data

This paper introduces a visualization method for time-course metabolomics data integrated into metabolic network maps, demonstrating its utility in analyzing platelet and erythrocyte storage.

The Escherichia coli Transcriptome Mostly Consists of Independently Regulated Modules

The paper decomposes the Escherichia coli transcriptome into 70 independent regulatory signals, showing that 50 correspond to known transcriptional regulators and revealing a principle of signal summation in prokaryotic gene regulation.

Systems-level physiology of the human red blood cell is computed from metabolic and macromolecular mechanisms

The paper develops a multi-scale computational model of human red blood cells integrating metabolic networks, proteomics, and macromolecular mechanisms to predict physiological quantities.

Experimental evolution reveals the genetic basis and systems biology of superoxide stress tolerance

This study uses adaptive laboratory evolution to generate E. coli strains with increased superoxide stress tolerance and identifies genetic and transcriptomic mechanisms underlying this adaptation.

DynamicME: Dynamic simulation and refinement of integrated models of metabolism and protein expression

DynamicME simulates and refines integrated metabolism and protein expression models using time-course data, accurately predicting substrate utilization and expression profiles.

Cellular responses to reactive oxygen species can be predicted on multiple biological scales from molecular mechanisms

The paper develops a quantitative framework to predict ROS stress responses in E. coli across molecular, network, and genetic levels.

COBRAme: A Computational Framework for Models of Metabolism and Gene Expression

COBRAme is a software framework for building and simulating ME-models, enabling efficient reconstruction and analysis of genome-scale models of metabolism and gene expression.