AIMC Topic: Metabolomics

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Primal-dual for classification with rejection (PD-CR): a novel method for classification and feature selection-an application in metabolomics studies.

BMC bioinformatics Dec 15, 2021
BACKGROUND: Supervised classification methods have been used for many years for feature selection in metabolomics and other omics studies. We developed a novel primal-dual based classification method (PD-CR) that can perform classification with rejec...
Support Vector Machine Humans Metabolomics Least-Squares Analysis Discriminant Analysis
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Graphene oxide enhanced the endocrine disrupting effects of bisphenol A in adult male zebrafish: Integrated deep learning and metabolomics studies.

The Science of the total environment Oct 29, 2021
In our previous studies, it was found that graphene oxide (GO) reduced the endocrine disruption of bisphenol A (BPA) in zebrafish embryo and larvae, but through different mechanisms. In this study, adult male zebrafish were selected to further unders...
Water Pollutants, Chemical Animals Benzhydryl Compounds Molecular Docking Simulation Metabolomics Endocrine Disruptors Male Zebrafish Deep Learning Phenols Graphite
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Deep learning allows genome-scale prediction of Michaelis constants from structural features.

PLoS biology Oct 19, 2021
The Michaelis constant KM describes the affinity of an enzyme for a specific substrate and is a central parameter in studies of enzyme kinetics and cellular physiology. As measurements of KM are often difficult and time-consuming, experimental estima...
Metabolomics Kinetics Models, Biological Substrate Specificity Neural Networks, Computer Deep Learning Databases, Genetic Genome Enzymes
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Peak learning of mass spectrometry imaging data using artificial neural networks.

Nature communications Sep 20, 2021
Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size ...
Mice Kidney Disease Models, Animal Nonlinear Dynamics Connective Tissue Metabolomics Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Animals Neoplasms Deep Learning Imaging, Three-Dimensional Neural Networks, Computer alpha-Defensins Humans Algorithms Reproducibility of Results
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Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis.

Scientific reports Sep 7, 2021
The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed model...
Hypertension, Pregnancy-Induced Pregnancy Complications Parity Gestational Age Adult Maternal Age Body Mass Index Japan Gas Chromatography-Mass Spectrometry Prospective Studies Metabolomics Humans Pregnancy Models, Biological Machine Learning Female Infant, Newborn
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Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.

BMC pregnancy and childbirth Sep 7, 2021
BACKGROUND: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, ad...
Developing Countries Africa South of the Sahara Neonatal Screening Gestational Age Cohort Studies ROC Curve Metabolomics Asia Prospective Studies Pregnancy Female Male Ultrasonography, Prenatal Infant, Newborn Premature Birth Humans Machine Learning Algorithms
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DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra.

Nature communications Sep 1, 2021
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Her...
Deep Learning Magnetic Resonance Imaging Metabolomics Proteins Neural Networks, Computer Algorithms Automation Nuclear Magnetic Resonance, Biomolecular Magnetic Resonance Spectroscopy
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EVA: Evaluation of Metabolic Feature Fidelity Using a Deep Learning Model Trained With Over 25000 Extracted Ion Chromatograms.

Analytical chemistry Aug 28, 2021
Extracting metabolic features from liquid chromatography-mass spectrometry (LC-MS) data relies on the recognition of extracted ion chromatogram (EIC) peak shapes using peak picking algorithms. Unfortunately, all peak picking algorithms present a sign...
Deep Learning Mass Spectrometry Metabolomics Chromatography, Liquid Algorithms
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Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza.

EBioMedicine Aug 19, 2021
BACKGROUND: Respiratory virus infections are significant causes of morbidity and mortality, and may induce host metabolite alterations by infecting respiratory epithelial cells. We investigated the use of liquid chromatography quadrupole time-of-flig...
Child, Preschool Child Molecular Diagnostic Techniques Metabolomics Adult Machine Learning Male Female Adolescent Humans Orthomyxoviridae Nasal Mucosa Pyrrolidonecarboxylic Acid Metabolome Influenza, Human Gas Chromatography-Mass Spectrometry
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An Improved Stacked Autoencoder for Metabolomic Data Classification.

Computational intelligence and neuroscience Aug 15, 2021
Naru3 (NR) is a traditional Mongolian medicine with high clinical efficacy and low incidence of side effects. Metabolomics is an approach that can facilitate the development of traditional drugs. However, metabolomic data have a high throughput, spar...
Support Vector Machine Algorithms Animals Metabolomics Mice
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