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GIM3E specifications

Information


Unique identifier OMICS_14740
Name GIM3E
Alternative name Gene Inactivation Moderated by Metabolism Metabolomics and Expression
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Python
Computer skills Advanced
Version 1.0.3
Stability Stable
Requirements
COBRApy
Maintained Yes

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Documentation


Maintainer


  • person_outline Brian Schmidt

Publication for Gene Inactivation Moderated by Metabolism Metabolomics and Expression

GIM3E citations

 (8)
library_books

MUFINS: multi formalism interaction network simulator

2016
NPJ Syst Biol Appl
PMCID: 5516860
PMID: 28725480
DOI: 10.1038/npjsba.2016.32

[…] nd validated in Use Case 1. In addition to the basic CBM methods available in SurreyFBA, the sfba engine of MUFINS implements a large number of ~omics data integration algorithms such as iMAT, GIMME, GIM3E, GNI and our DPA. The GNI and DPA features of sfba have been already used to study Mycobacterium tuberculosis metabolism. Furthermore, we include Fast iMAT a new variant of iMAT approach demonst […]

library_books

Benchmarking Procedures for High Throughput Context Specific Reconstruction Algorithms

2016
Front Physiol
PMCID: 4722106
PMID: 26834640
DOI: 10.3389/fphys.2015.00410

[…] ining functionality is the same. Since we wanted to focus on gene expression data, which is currently the most readily available type of data, we did not add metabolomic information into our screens. GIM3E would need this type of information and was therefore not tested. Finally, MBA, Lee and mCADRE took more than 5 days for a single run on 2 cores of our cluster and where therefore not included. […]

library_books

Integration of metabolomics data into metabolic networks

2015
Front Plant Sci
PMCID: 4330704
PMID: 25741348
DOI: 10.3389/fpls.2015.00049

[…] Another approach for context-specific network extraction is Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression (GIM3E) (Schmidt et al., ). GIM3E is an extension to GIMME (Becker and Palsson, ), a network extraction approach that integrates […]

library_books

Integrated network analysis and effective tools in plant systems biology

2014
Front Plant Sci
PMCID: 4219401
PMID: 25408696
DOI: 10.3389/fpls.2014.00598

[…] ctivity of an enzyme. The first, E-FLUX (Colijn et al., ), uses maximum flux constraints as a function of measured transcript levels without binalization of the expression data. The other approach is GIM3E, it does not apply arbitrary cutoffs for expression levels (Schmidt et al., ). Protein data can also be included. PROM (Chandrasekaran and Price, ) invokes a threshold to determine whether an en […]

library_books

Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome scale metabolic model

2014
Biotechnol Biofuels
PMCID: 4207355
PMID: 25379054
DOI: 10.1186/s13068-014-0144-4

[…] grated metabolic and regulatory models []. PROM uses a probabilistic description of gene states and gene-transcription factor interactions while integrating heterogeneous high-throughput data []. The GIM3E method penalizes the flux for reactions whose associated genes have low expression levels in the transcriptome []. The recently proposed MTA method identifies minimal transformation rules from o […]

library_books

Generalized framework for context specific metabolic model extraction methods

2014
Front Plant Sci
PMCID: 4168813
PMID: 25285097
DOI: 10.3389/fpls.2014.00491

[…] e computational platform of the current implementations, or the difference in computing time. For instance, the choice is between the COBRA toolbox in Matlab, for GIMME, or its version in Python, for GIM3E (“The OpenCOBRA Project,” ), or between the LP formulation of GIMME, vs. the more computationally demanding MILP of GIM3E.Without the information about the operability of a particular RMF in a g […]

Citations

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GIM3E institution(s)
Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA; Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
GIM3E funding source(s)
This work was supported in part by the US National Institute of Allergy and Infectious Diseases and the US Department of Health and Human Services through interagency agreement (Y1-AI-8401-01).

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