Predicting the pathway involvement of metabolites annotated in the MetaCyc knowledgebase

These performance results are pragmatically the same, demonstrating that in aggregate, the 4055 MetaCyc pathways can be effectively predicted at the current state-of-the-art performance level.

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Publication Details

Journal
BMC Bioinformatics
Published
2026-01-07
DOI
https://doi.org/10.1186/s12859-025-06358-z
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
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article

Predicting the pathway involvement of metabolites annotated in the MetaCyc knowledgebase

Erik D. Huckvale, Hunter N. B. Moseley
BMC Bioinformatics
Bioinformatics and Genomic Networks
article

Predicting the pathway involvement of metabolites annotated in the MetaCyc knowledgebase

Erik D. Huckvale, Hunter N. B. Moseley
article en

Abstract

These performance results are pragmatically the same, demonstrating that in aggregate, the 4055 MetaCyc pathways can be effectively predicted at the current state-of-the-art performance level.

BMC BioinformaticsVol. 27(1)
University of Kentucky (US), Markey Cancer Center (US)
Openalex Percentile: Top 94%
Bioinformatics and Genomic Networks
DOIOpen Access PDFOpenAlex
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Predicting the pathway involvement of metabolites annotated in the MetaCyc knowledgebase — Erik D. Huckvale, Hunter N. B. Moseley · BMC Bioinformatics (2026) | TGRS Research Map | TGRS