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A cautionary tale about properly vetting datasets used in supervised learning predicting metabolic pathway involvement.
PLoS One. 2024 May 2;19(5):e0299583. doi: 10.1371/journal.pone.0299583. eCollection 2024.
PLoS One. 2024.
PMID: 38696410
Free PMC article.
Predicting The Pathway Involvement Of Metabolites Based on Combined Metabolite and Pathway Features.
Huckvale ED, Moseley HNB.
Huckvale ED, et al.
bioRxiv [Preprint]. 2024 Apr 2:2024.04.01.587582. doi: 10.1101/2024.04.01.587582.
bioRxiv. 2024.
PMID: 38617261
Free PMC article.
Preprint.
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Benchmark Dataset for Training Machine Learning Models to Predict the Pathway Involvement of Metabolites.
Huckvale ED, Powell CD, Jin H, Moseley HNB.
Huckvale ED, et al.
Metabolites. 2023 Nov 1;13(11):1120. doi: 10.3390/metabo13111120.
Metabolites. 2023.
PMID: 37999216
Free PMC article.
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Benchmark dataset for training machine learning models to predict the pathway involvement of metabolites.
Huckvale ED, Powell CD, Jin H, Moseley HNB.
Huckvale ED, et al.
bioRxiv [Preprint]. 2023 Oct 9:2023.10.03.560715. doi: 10.1101/2023.10.03.560715.
bioRxiv. 2023.
PMID: 37873272
Free PMC article.
Updated.
Preprint.
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Pairwise Correlation Analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset Reveals Significant Feature Correlation.
Huckvale ED, Hodgman MW, Greenwood BB, Stucki DO, Ward KM, Ebbert MTW, Kauwe JSK, The Alzheimer's Disease Neuroimaging Initiative, The Alzheimer's Disease Metabolomics Consortium, Miller JB.
Huckvale ED, et al.
Genes (Basel). 2021 Oct 21;12(11):1661. doi: 10.3390/genes12111661.
Genes (Basel). 2021.
PMID: 34828267
Free PMC article.
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