Universität zu Köln

Saadat, Nima P., van Aalst, Marvin ORCID: 0000-0002-7434-0249 and Ebenhoeh, Oliver ORCID: 0000-0002-7229-7398 (2022). Network Reconstruction and Modelling Made Reproducible with moped. Metabolites, 12 (4). BASEL: MDPI. ISSN 2218-1989

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Abstract

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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Saadat, Nima P. UNSPECIFIED UNSPECIFIED UNSPECIFIED van Aalst, Marvin UNSPECIFIED orcid.org/0000-0002-7434-0249 UNSPECIFIED Ebenhoeh, Oliver UNSPECIFIED orcid.org/0000-0002-7229-7398 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-663718
DOI:	10.3390/metabo12040275
Journal or Publication Title:	Metabolites
Volume:	12
Number:	4
Date:	2022
Publisher:	MDPI
Place of Publication:	BASEL
ISSN:	2218-1989
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language COMPLETE GENOME SEQUENCE; METABOLIC NETWORKS Multiple languages Biochemistry & Molecular Biology Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/66371