Next Article in Journal
MetaboListem and TABoLiSTM: Two Deep Learning Algorithms for Metabolite Named Entity Recognition
Next Article in Special Issue
A Genome-Scale Metabolic Model of Methanoperedens nitroreducens: Assessing Bioenergetics and Thermodynamic Feasibility
Previous Article in Journal
Selenium Levels and Antioxidant Activity in Critically Ill Patients with Systemic Inflammatory Response Syndrome
 
 
Article

Network Reconstruction and Modelling Made Reproducible with moped

by 1,†, 1,† and 1,2,*
1
Institute of Quantitative and Theoretical Biology, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany
2
Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Oscar Dias, Hunter N. B. Moseley and Miguel Rocha
Metabolites 2022, 12(4), 275; https://doi.org/10.3390/metabo12040275
Received: 14 December 2021 / Revised: 24 February 2022 / Accepted: 15 March 2022 / Published: 22 March 2022
(This article belongs to the Special Issue Reconstruction of Genome-Scale Metabolic Models)
Mathematical modeling of metabolic networks is a powerful approach to investigate the underlying principles of metabolism and growth. Such approaches include, among others, differential-equation-based modeling of metabolic systems, constraint-based modeling and metabolic network expansion of metabolic networks. Most of these methods are well established and are implemented in numerous software packages, but these are scattered between different programming languages, packages and syntaxes. This complicates establishing straight forward pipelines integrating model construction and simulation. We present a Python package moped that serves as an integrative hub for reproducible construction, modification, curation and analysis of metabolic models. moped supports draft reconstruction of models directly from genome/proteome sequences and pathway/genome databases utilizing GPR annotations, providing a completely reproducible model construction and curation process within executable Python scripts. Alternatively, existing models published in SBML format can be easily imported. Models are represented as Python objects, for which a wide spectrum of easy-to-use modification and analysis methods exist. The model structure can be manually altered by adding, removing or modifying reactions, and gap-filling reactions can be found and inspected. This greatly supports the development of draft models, as well as the curation and testing of models. Moreover, moped provides several analysis methods, in particular including the calculation of biosynthetic capacities using metabolic network expansion. The integration with other Python-based tools is facilitated through various model export options. For example, a model can be directly converted into a CobraPy object for constraint-based analyses. moped is a fully documented and expandable Python package. We demonstrate the capability to serve as a hub for integrating reproducible model construction and curation, database import, metabolic network expansion and export for constraint-based analyses. View Full-Text
Keywords: metabolic networks; modeling; topological networks; metabolic network expansion; network reconstruction metabolic networks; modeling; topological networks; metabolic network expansion; network reconstruction
Show Figures

Figure 1

MDPI and ACS Style

Saadat, N.P.; van Aalst, M.; Ebenhöh, O. Network Reconstruction and Modelling Made Reproducible with moped. Metabolites 2022, 12, 275. https://doi.org/10.3390/metabo12040275

AMA Style

Saadat NP, van Aalst M, Ebenhöh O. Network Reconstruction and Modelling Made Reproducible with moped. Metabolites. 2022; 12(4):275. https://doi.org/10.3390/metabo12040275

Chicago/Turabian Style

Saadat, Nima P., Marvin van Aalst, and Oliver Ebenhöh. 2022. "Network Reconstruction and Modelling Made Reproducible with moped" Metabolites 12, no. 4: 275. https://doi.org/10.3390/metabo12040275

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop