• Publications
  • Influence
COBRAme: A computational framework for genome-scale models of metabolism and gene expression
TLDR
COBRAme provides tools to simplify constructing and editing ME-models to enable ME-model reconstructions for new organisms and is used to reconstruct a condensed E. coli ME- model called iJL1678b-ME.
Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance
TLDR
A reference strain-agnostic computational platform is developed that uses machine learning approaches, complemented by both genetic interaction analysis and 3D structural mutation-mapping, to identify signatures of AMR evolution to 13 antibiotics.
The Escherichia coli transcriptome mostly consists of independently regulated modules
TLDR
Unsupervised machine learning is applied to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets and finds that most gene sets represent the effects of specific transcriptional regulators.
Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data
TLDR
This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.
DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression
TLDR
DynamicME provides a novel method for understanding proteome allocation and metabolism under complex and transient environments, and to utilize time-course cell culture data for model-based interpretation or model refinement.
Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655
TLDR
An integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments is developed and demonstrated how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel.
Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655
TLDR
An integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments is developed and results demonstrate how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel.
Cellular responses to reactive oxygen species are predicted from molecular mechanisms
TLDR
A computable multiscale description of the ROS stress response in Escherichia coli is developed, called OxidizeME, which shows that fundamental and quantitative genotype–phenotype relationships for stress responses on a genome-wide basis are developed.
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