MMinte statistics

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Citations per year

Number of citations per year for the bioinformatics software tool MMinte
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Tool usage distribution map

This map represents all the scientific publications referring to MMinte per scientific context
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MMinte specifications

Information


Unique identifier OMICS_12841
Name MMinte
Alternative name Microbial Metabolic Interactions
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Input format TXT, FASTA
Output data Network diagram representing the interactions between the pairs of species.
Operating system Unix/Linux, Windows
Programming languages Python
License BSD 3-clause “New” or “Revised” License
Computer skills Advanced
Version 1.3
Stability Stable
Requirements
BioPython, CherryPy, Cobra, Cycler, DataSpyre, Jinja2, MarkupSafe, Numpy, Pandas, Pyparsing, Python-dateutil, Pytz, Scipy, Six, Wheel
Maintained Yes

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Documentation


Maintainer


  • person_outline Nicholas Chia

Publication for Microbial Metabolic Interactions

MMinte citation

library_books

Parametric studies of metabolic cooperativity in Escherichia coli colonies: Strain and geometric confinement effects

2017
PLoS One
PMCID: 5562313
PMID: 28820904
DOI: 10.1371/journal.pone.0182570

[…] trated the potential for cross-feeding in the gut microbiome in idealized populations []. Further, a number of tools/databases that identify metabolic cross-feeding from metagenomic datasets (such as MMinte [] and AGORA []) are now available. These will help inform construction of realistic model gut communities. Such studies could lead to insights into community dynamics, and potentially, their c […]


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MMinte institution(s)
Microbiome Program, Center for Individualized Medicine, Mayo Clinic, Chinahester, MN, USA; Department of Surgery, Mayo Clinic, Chinahester, MN, USA; Microbiome Program, Center for Individualized Medicine, Mayo Clinic, Chinahester, MN, USA; Harvard Medical School, Boston, MA, USA; Microbiome Program, Center for Individualized Medicine, Mayo Clinic, Chinahester, MN, USA; Department of Surgery, Mayo Clinic, Chinahester, MN, USA; Department of Physiology and Biomedical Engineering, Mayo College, Chinahester, MN, USA
MMinte funding source(s)
This work was supported by the Mayo Clinic Center for Individualized Medicine and the National Institutes of Health under award number R01CA179243.

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