ArticlePLoS computational biology2010
An automated phenotype-driven approach (GeneForce) for refining metabolic and regulatory models.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Visualization of Self-Assembly and Hydration of a β-Hairpin through Integrated Small and Wide-Angle Neutron Scattering.Biomacromolecules · 2023Article
- Genome-scale metabolic reconstruction of the non-model yeastMetabolic engineering communications · 2020Article
- Article
- Systems Metabolic Engineering of Escherichia coli Improves Coconversion of Lignocellulose-Derived Sugars.Biotechnology journal · 2019Article
- The landscape of microbial phenotypic traits and associated genes.Nucleic acids research · 2016Article
- MapMaker and PathTracer for tracking carbon in genome-scale metabolic models.Biotechnology journal · 2016Article
- PSAMM: A Portable System for the Analysis of Metabolic Models.PLoS computational biology · 2016Article
- Review
- Data-driven integration of genome-scale regulatory and metabolic network models.Frontiers in microbiology · 2015Review
- A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database.BMC systems biology · 2014Article
- Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model.Biotechnology for biofuels · 2014Article
- Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods.BMC proceedings · 2014Article
- Global insights into energetic and metabolic networks in Rhodobacter sphaeroides.BMC systems biology · 2013Article
- Multiscale computational models of complex biological systems.Annual review of biomedical engineering · 2013Review
- Metabolic constraint-based refinement of transcriptional regulatory networks.PLoS computational biology · 2013Article
- BioMog: a computational framework for the de novo generation or modification of essential biomass components.PloS one · 2013Article
- Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli.Molecular systems biology · 2013Review
- Systematic applications of metabolomics in metabolic engineering.Metabolites · 2012Article
- FOCAL: an experimental design tool for systematizing metabolic discoveries and model development.Genome biology · 2012Article
- Reverse engineering systems models of regulation: discovery, prediction and mechanisms.Current opinion in biotechnology · 2012Review
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3 authors.
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Abstract
Integrated constraint-based metabolic and regulatory models can accurately predict cellular growth phenotypes arising from genetic and environmental perturbations. Challenges in constructing such models involve the limited availability of information about transcription factor--gene target interactions and computational methods to quickly refine models based on additional datasets. In this study, we developed an algorithm, GeneForce, to identify incorrect regulatory rules and gene-protein-reaction associations in integrated metabolic and regulatory models. We applied the algorithm to refine integrated models of Escherichia coli and Salmonella typhimurium, and experimentally validated some of the algorithm's suggested refinements. The adjusted E. coli model showed improved accuracy (∼80.0%) for predicting growth phenotypes for 50,557 cases (knockout mutants tested for growth in different environmental conditions). In addition to identifying needed model corrections, the algorithm was used to identify native E. coli genes that, if over-expressed, would allow E. coli to grow in new environments. We envision that this approach will enable the rapid development and assessment of genome-scale metabolic and regulatory network models for less characterized organisms, as such models can be constructed from genome annotations and cis-regulatory network predictions.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.