Benchmark dataset for training machine learning models to predict the pathway involvement of metabolites.

ABSTRACT: Metabolic pathways are a human-defined grouping of life sustaining biochemical reactions, metabolites being both the reactants and products of these reactions. But many public datasets include identified metabolites whose pathway involvement is unknown, hindering metabolic interpretation. To address these shortcomings, various machine learning models, including those trained on data from the Kyoto Encyclopedia of Genes and Genomes (KEGG), have been developed to predict the pathway involvement of metabolites based on their chemical descriptions; however, these prior models are based on old metabolite KEGG-based datasets, including one benchmark dataset that is invalid due to the presence of over 1500 duplicate entries. Therefore, we have developed a new benchmark dataset derived from the KE

SUBMITTER: Huckvale ED 

PROVIDER: S-EPMC10592640 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature