ArticleMolecular systems biology2014
An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli.
Article in Molecular systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Multiscale Mathematical Modeling in Systems Biology: A Framework to Boost Plant Synthetic Biology.Plants (Basel, Switzerland) · 2025Review
- Article
- Genome-wide promoter responses to CRISPR perturbations of regulators reveal regulatory networks in Escherichia coli.Nature communications · 2023Article
- An expanded whole-cell model of E. coli links cellular physiology with mechanisms of growth rate control.NPJ systems biology and applications · 2022Article
- Genome-scale metabolic network models: from first-generation to next-generation.Applied microbiology and biotechnology · 2022Review
- A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling.Nature communications · 2022Article
- Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.Biomolecules · 2022Review
- Protocol for condition-dependent metabolite yield prediction using the TRIMER pipeline.STAR protocols · 2022Article
- Using genome-wide expression compendia to study microorganisms.Computational and structural biotechnology journal · 2022Review
- Article
- Review
- Multiscale plant modeling: from genome to phenome and beyond.Emerging topics in life sciences · 2021Review
- Advances in flux balance analysis by integrating machine learning and mechanism-based models.Computational and structural biotechnology journal · 2021Review
- Article
- Reconstructing organisms in silico: genome-scale models and their emerging applications.Nature reviews. Microbiology · 2020Review
- Simultaneous cross-evaluation of heterogeneousScience (New York, N.Y.) · 2020Article
- iMTBGO: An Algorithm for Integrating Metabolic Networks with Transcriptomes Based on Gene Ontology Analysis.Current genomics · 2019Article
- Predicting growth rate from gene expression.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a common framework the various biological processes and their interactions across multiple layers. We trained this methodology on an extensive normalized compendium for the gram-negative bacterium Escherichia coli, which incorporates gene expression data for genetic and environmental perturbations, transcriptional regulation, signal transduction, and metabolic pathways, as well as growth measurements. Comparison with measured growth and high-throughput data demonstrates the enhanced ability of the integrative model to predict phenotypic outcomes in various environmental and genetic conditions, even in cases where their underlying functions are under-represented in the training set. This work paves the way toward integrative techniques that extract knowledge from a variety of biological data to achieve more than the sum of their parts in the context of prediction, analysis, and redesign of biological systems.
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Registered trials
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