md_harmonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases

Huan Jin; Hunter N.B. Moseley

doi:10.3390/metabo13121199

md_harmonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases

Huan Jin, Hunter N.B. Moseley

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

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.

Original language	English
Article number	1199
Journal	Metabolites
Volume	13
Issue number	12
DOIs	https://doi.org/10.3390/metabo13121199
State	Published - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

Funding

The research was funded by the United States National Science Foundation (NSF), grant number 2020026.

Funders	Funder number
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China	2020026
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China

Keywords

Python package
database harmonization
maximum common substructure
metabolite

ASJC Scopus subject areas

Endocrinology, Diabetes and Metabolism
Biochemistry
Molecular Biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3390/metabo13121199

Cite this

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title = "md\_harmonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases",

abstract = "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{\textquoteright}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.",

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doi = "10.3390/metabo13121199",

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volume = "13",

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AB - 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.

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md_harmonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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