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Metabolome

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Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet.

Scientific reports
Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data collection with relative ease. This is accompanied by a fast-growing demand for technological progress...

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide ex...

Predicting novel substrates for enzymes with minimal experimental effort with active learning.

Metabolic engineering
Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of ...

Metabolite Profiling of ADB-FUBINACA, A New Synthetic Cannabinoid.

Current neuropharmacology
Metabolite profiling of novel psychoactive substances (NPS) is critical for documenting drug consumption. N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(4-fluorobenzyl)-1H-indazole-3-carboxamide (ADB-FUBINACA) is an emerging synthetic cannabinoid whose ...

Meta-learning framework applied in bioinformatics inference system design.

International journal of data mining and bioinformatics
This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates...