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md_(h)armonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases
by
Moseley, Hunter N. B
, Jin, Huan
in
Analysis
/ Data mining
/ database harmonization
/ Evaluation
/ maximum common substructure
/ metabolite
/ Metabolomics
/ Nuclear magnetic resonance spectroscopy
/ Python (Programming language)
/ Python package
2023
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md_(h)armonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases
by
Moseley, Hunter N. B
, Jin, Huan
in
Analysis
/ Data mining
/ database harmonization
/ Evaluation
/ maximum common substructure
/ metabolite
/ Metabolomics
/ Nuclear magnetic resonance spectroscopy
/ Python (Programming language)
/ Python package
2023
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Do you wish to request the book?
md_(h)armonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases
by
Moseley, Hunter N. B
, Jin, Huan
in
Analysis
/ Data mining
/ database harmonization
/ Evaluation
/ maximum common substructure
/ metabolite
/ Metabolomics
/ Nuclear magnetic resonance spectroscopy
/ Python (Programming language)
/ Python package
2023
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md_(h)armonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases
Journal Article
md_(h)armonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases
2023
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Overview
A major challenge to integrating public metabolic resources is the use of different nomenclatures by individual databases. This paper presents md_harmonize, an open-source Python package for harmonizing compounds and metabolic reactions across various metabolic databases. The md_harmonize package utilizes a neighborhood-specific graph coloring method for generating a unique identifier for each compound via atom identifiers based on a compound’s chemical structure. The resulting harmonized compounds and reactions can be used for various downstream analyses, including the construction of atom-resolved metabolic networks and models for metabolic flux analysis. Parts of the md_harmonize package have been optimized using a variety of computational techniques to allow certain NP-complete problems handled by the software to be tractable for these specific use-cases. The software is available on GitHub and through the Python Package Index, with end-user documentation hosted on GitHub Pages.
Publisher
MDPI AG
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