High-throughput generation, optimization and analysis of genome-scale metabolic models

By Christopher S. Henry, M. DeJongh, Aaron A. Best, Paul Frybarger, Ben Linsay, Rick L. Stevens. Nature Biotechnology, 2010

1,067 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9292be78da29918337eae63981522bed7e7a707f

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Citations in the corpus

Using Genome-Scale Models to Predict Biological Capabilities (2015, neutral): “…the COBRA Toolbox (Ebrahim et al., 2013; Schellenberger et al., 2011b), KEGG (Kanehisa et al., 2014), EcoCyc (Keseler et al., 2013), ModelSeed (Henry et al., 2010b), BiGG (Schellenberger et al., 2010), Rbionet(Thorleifssonand Thiele, 2011),Subliminal (Swainston et al., 2011), Raven toolbox…”
COBRApy: COnstraints-Based Reconstruction and Analysis for Python (2013, methodology): “Additionally, COBRApy can read SBML-formatted models [32] downloaded from a variety of sources, such as the Model SEED [33] and the BioModels database [34].”
The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum (2013, methodology): “Even though the RAVEN Toolbox can be used for fully automated reconstruction, in a manner similar to Model SEED, the intended purpose is to make use of the extensive quality control and gap identification/gap filling features for increasing the quality of reconstructions, as well as for decreasing t”
The Role of Soil Microorganisms in Plant Mineral Nutrition—Current Knowledge and Future Directions (2017, methodology): “In an automated process of mining the information from databases (Henry et al., 2010), the enzymes encoded in the genome are assigned metabolic functions.”
A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011 (2011, methodology): “Comparison of iJO1366 to the Model SEED E. coli reconstruction The E. coli K-12 MG1655 model Seed83333.”
The Potential of Metagenomic Approaches for Understanding Soil Microbial Processes (2014, background): “Another option would be to extend metabolic modeling of individual organisms (Henry et al., 2010) to soil microbial communities, as has been done for simpler systems (Stolyar et al.”
Big Data Analytics in Healthcare (2015, methodology): “Available reconstructed metabolic networks include Recon 1 [161], Recon 2 [150], SEED [163], IOMA [165], and MADE [172].”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “…plug-in, CytoSEED Genome level metabolic network reconstruction and analysis https://github.com/ModelSEED, http:// sourceforge.net/projects/cytoseed Henry et al., 2010; DeJongh et al., 2012 Markov Chain Monte Carlo modeling Bayesian inference method to uncover perturbation sites in metabolic…”
Predicting Network Activity from High Throughput Metabolomics (2013, background): “The reconstruction of microbial metabolic network models is an established process [13,14].”
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015, background): “The external databases include KEGG (3), Meta-Cyc (4), Reactome (27), HMDB (21), RCSB PDB (28), Model SEED (29) and Entrez Gene (30).”
The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST) (2013, methodology): “(9) Any DNA stretches longer than 1500 bp that do not contain a gene are ‘backfilled’ with gene candidates by comparing them with the proteins from the 30 nearest neighbors using BLASTX (19).”
A genomic catalog of Earth’s microbiomes (2020, methodology): “GEMs and reference genomes were annotated with RAST [6] in KBase, as the ModelSEED pipeline uses RAST functional roles to map genes to biochemical reactions [7, 8] .”
RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes (2015, methodology): “It is also being used as the foundation for maintaining consistency for automated metabolic modeling in the ModelSEED 8 and KBase (kbase.us), and for comparative genomics in the bacterial pathogen database, PATRIC 9,10 .”
OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities (2012, methodology): “, however, this model had only a compact representation of the central metabolism. For example, the model was not able to support growth in the presence of acetate or ethanol as the sole carbon source. Therefore, we expanded this model by adding new reactions from a first draft reconstructed model i”
Insights from 20 years of bacterial genome sequencing (2015, methodology): “Another effort for high-throughput generation and analysis of GEMs has been developed under a Web-based environment called Model SEED (Henry et al. 2010).”