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Network Reconstruction and Modelling Made Reproducible with moped.

Nima P Saadat1, Marvin van Aalst1, Oliver Ebenhöh1,2

  • 1Institute of Quantitative and Theoretical Biology, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany.

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We developed moped, a Python package for reproducible metabolic model construction and analysis. It integrates various methods, streamlining pipelines for metabolic network expansion and constraint-based modeling.

Keywords:
metabolic network expansionmetabolic networksmodelingnetwork reconstructiontopological networks

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Metabolic Engineering

Background:

  • Metabolic network modeling is crucial for understanding metabolism and growth.
  • Existing modeling tools are fragmented across languages and syntaxes, hindering integrated pipelines.
  • A unified approach is needed for reproducible model construction, modification, and analysis.

Purpose of the Study:

  • To introduce moped, a Python package serving as an integrative hub for metabolic models.
  • To enable reproducible model construction, curation, and analysis within a single framework.
  • To facilitate integration with other computational biology tools.

Main Methods:

  • Developed moped as a Python package for metabolic model management.
  • Implemented direct draft reconstruction from genome/proteome data using GPR annotations.
  • Enabled import of existing models from SBML format.
  • Provided methods for model modification, gap-filling, and analysis, including metabolic network expansion.
  • Facilitated export to other formats, such as CobraPy objects.

Main Results:

  • moped offers a reproducible pipeline for metabolic model construction and curation.
  • The package supports manual model alteration and gap-filling reaction identification.
  • Biosynthetic capacities can be calculated using metabolic network expansion.
  • Seamless integration with constraint-based analysis tools like CobraPy is supported.
  • moped serves as a versatile hub for diverse metabolic modeling workflows.

Conclusions:

  • moped provides a unified and reproducible environment for metabolic modeling.
  • The package simplifies the integration of model construction, analysis, and export.
  • moped enhances the development and curation of metabolic models for systems biology research.