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Informed prediction and analysis of bacterial metabolic pathways and genome-scale networks

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gapseq

Informed prediction and analysis of bacterial metabolic pathways and genome-scale networks
Documentation Status DOI:10.1186/s13059-021-02295-1

gapseq is designed to combine metabolic pathway analysis with metabolic network reconstruction and curation. Based on genomic information and databases for pathways and reactions, gapseq can be used for:

  • prediction of metabolic pathways from various databases
  • transporter inference
  • metabolic model construction
  • multi-step gap filling

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Publication

Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biology 22, 81 (2021)

Installation

The latest release can be downloaded here. Besides this, the current development version can be accessed via:

git clone https://github.com/jotech/gapseq

Detailed information on installation and troubleshooting.

Quickstart

For detailed use cases and full tutorials, see the documentation.

Prediction of network candidate reactions, building of a draft model and gap filling:

./gapseq doall toy/myb71.fna

Do the same but with a defined medium for gap filling:

./gapseq doall toy/ecoli.fna.gz dat/media/MM_glu.csv

LICENSE

Copyright 2020 Johannes Zimmermann, Christoph Kaleta, & Silvio Waschina; University of Kiel, Germany

GNU General Public License version 3.0 (GPLv3) is applied to all copyrightable parts of gapseq. gapseq uses information on biochemical reactions, compounds, compartments, enzymes, and biological sequences from different external sources. The copyright and licensing terms for each of the resources are listed and cross-linked below. Identifiers for reactions, enzymes, compounds, and compartments may be identical to the external sources but can also differ to those. In both cases, the data from gapseq may be considered to be subject to the original copyright and licensing restrictions of the external resource.

Citation

  • Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1
  • De Bernardini, N., Zampieri, G., Campanaro, S., Zimmermann, J., Waschina, S. & Treu, L. pan-Draft: Automated reconstruction of species-representative metabolic models from multiple genomes. Currently under revision