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zenodo.yml
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zenodo.yml
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creators:
- name: Diener, Christian
affiliation: Institute for Systems Biology
orcid: 0000-0002-7476-0868
version: "1"
upload_type: dataset
access_right: open
license: cc-by-sa
description: |
This repository includes pre-built model databases for the microbial community
modeling tool MICOM (https://micom-dev.github.io/micom). All model databases will
work with the MICOM python package or the MICOM Qiime 2 plugin
(http://github.com/micom-dev/q2-micom).<br><br>
The Zenodo release is built and versioned automatically from the the source
repository at http://github.com/micom-dev/databases. Thus, all bug reports, requests,
and comments should be made there.<br>
<hr>
Model databases are named with the following scheme:<br>
SOURCE_SVER_TAXONOMY_TVER_RANK_VERSION.qza<br>
where:<br>
<ul>
<li>SOURCE = source database for the models</li>
<li>SVER = version of the source database</li>
<li>TAXONOMY = the taxonomy naming scheme used</li>
<li>TVER = the version of the taxonomy naming scheme</li>
<li>RANK = the taxonomic rank models were collapsed on</li>
<li>VERSION = the version of the built database</li>
</ul>
<hr>
For all practical purposes the TAXONOMY should coincide with the taxonomic classification
of your amplicons or genomes. For instance, if you used kraken2 and bracken2 you should
use a model database with TAXONOMY = ncbi. Note that some taxonomy databases (GTDB, GreenGenes)
prefix taxonomy identifiers with a rank indentifier like `s__Species`. Those are usually maintained
in the databases here except for the NCBI Taxonomy which usually does not use those. You can
verify taxon names using the manifests in the `release` section of http://github.com/micom-dev/databases .
<br><br>
For growth media that can be used with the model databases here please see the MICOM
media repository at https://github.com/micom-dev/media.
references:
- >
Diener C, Gibbons SM, Resendis-Antonio O.
MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota.
mSystems. 2020 Jan 21;5(1):e00606-19.
doi: 10.1128/mSystems.00606-19. PMID: 31964767; PMCID: PMC6977071
- >
Machado D, Andrejev S, Tramontano M, Patil KR.
Fast automated reconstruction of genome-scale metabolic models for microbial species and communities.
Nucleic Acids Res. 2018 Sep 6;46(15):7542-7553.
doi: 10.1093/nar/gky537. PMID: 30192979; PMCID: PMC6125623
- >
Magnúsdóttir S, Heinken A, Kutt L, Ravcheev DA, Bauer E, Noronha A, Greenhalgh K, Jäger C, Baginska J, Wilmes P, Fleming RM, Thiele I.
Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota.
Nat Biotechnol. 2017 Jan;35(1):81-89.
doi: 10.1038/nbt.3703. Epub 2016 Nov 28. PMID: 27893703
- >
Zimmermann, J., Kaleta, C. & Waschina, S.
gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models.
Genome Biol 22, 81 (2021).
doi: 10.1186/s13059-021-02295-1
- >
Heinken, A., Hertel, J., Acharya, G. et al.
Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine.
Nat Biotechnol (2023).
doi: 10.1038/s41587-022-01628-0
- >
Almeida, A., Nayfach, S., Boland, M. et al.
A unified catalog of 204,938 reference genomes from the human gut microbiome.
Nat Biotechnol 39, 105–114 (2021).
doi: 10.1038/s41587-020-0603-3