AIMC Topic: Metabolomics

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Utilizing machine learning with knockoff filtering to extract significant metabolites in Crohn's disease with a publicly available untargeted metabolomics dataset.

PloS one Jul 29, 2021
Metabolomic data processing pipelines have been improving in recent years, allowing for greater feature extraction and identification. Lately, machine learning and robust statistical techniques to control false discoveries are being incorporated into...
Metabolome Humans Crohn Disease Machine Learning Metabolomics
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Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets.

Scientific reports Jul 23, 2021
COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high thr...
Databases, Genetic Metabolomics Databases, Factual Immunity, Innate Biomarkers Databases, Protein Interferon-gamma Computer Simulation Machine Learning Severity of Illness Index Prognosis Humans Software Gene Expression Profiling ROC Curve SARS-CoV-2 COVID-19 Proteomics Signal Transduction
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SCOUR: a stepwise machine learning framework for predicting metabolite-dependent regulatory interactions.

BMC bioinformatics Jul 8, 2021
BACKGROUND: The topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms-t...
Gene Regulatory Networks Metabolomics Metabolic Networks and Pathways Gene Expression Regulation Machine Learning Algorithms
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SMILE: systems metabolomics using interpretable learning and evolution.

BMC bioinformatics May 28, 2021
BACKGROUND: Direct link between metabolism and cell and organism phenotype in health and disease makes metabolomics, a high throughput study of small molecular metabolites, an essential methodology for understanding and diagnosing disease development...
Computational Biology Metabolomics Machine Learning Algorithms
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Aging-related markers in rat urine revealed by dynamic metabolic profiling using machine learning.

Aging May 19, 2021
The process of aging and metabolism is intimately intertwined; thus, developing biomarkers related to metabolism is critical for delaying aging. However, few studies have identified reliable markers that reflect aging trajectories based on machine le...
Algorithms Biomarkers Animals Machine Learning Rats, Wistar Rats Metabolomics Metabolome Aging Neoplasms Time Factors Body Weight Feeding Behavior
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Pure Ion Chromatograms Combined with Advanced Machine Learning Methods Improve Accuracy of Discriminant Models in LC-MS-Based Untargeted Metabolomics.

Molecules (Basel, Switzerland) May 5, 2021
Untargeted metabolomics based on liquid chromatography coupled with mass spectrometry (LC-MS) can detect thousands of features in samples and produce highly complex datasets. The accurate extraction of meaningful features and the building of discrimi...
Chromatography, Liquid Principal Component Analysis Discriminant Analysis Colonic Neoplasms Tandem Mass Spectrometry ROC Curve Models, Theoretical Metabolomics Algorithms Male Middle Aged Machine Learning Humans Data Analysis
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Exploring photoacoustic spectroscopy-based machine learning together with metabolomics to assess breast tumor progression in a xenograft model ex vivo.

Laboratory investigation; a journal of technical methods and pathology Apr 19, 2021
In the current study, a breast tumor xenograft was established in athymic nude mice by subcutaneous injection of the MCF-7 cell line and assessed the tumor progression by photoacoustic spectroscopy combined with machine learning tools. The advancemen...
Machine Learning Algorithms Humans MCF-7 Cells Mice Photoacoustic Techniques Female Image Interpretation, Computer-Assisted Mice, Nude Metabolomics Breast Neoplasms Spectrum Analysis Mammary Neoplasms, Experimental Animals
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SteroidXtract: Deep Learning-Based Pattern Recognition Enables Comprehensive and Rapid Extraction of Steroid-Like Metabolic Features for Automated Biology-Driven Metabolomics.

Analytical chemistry Mar 30, 2021
Despite the vast amount of metabolic information that can be captured in untargeted metabolomics, many biological applications are looking for a biology-driven metabolomics platform that targets a set of metabolites that are relevant to the given bio...
Computational Biology Metabolomics Tandem Mass Spectrometry Steroids Deep Learning
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Using machine learning approaches for multi-omics data analysis: A review.

Biotechnology advances Mar 29, 2021
With the development of modern high-throughput omic measurement platforms, it has become essential for biomedical studies to undertake an integrative (combined) approach to fully utilise these data to gain insights into biological systems. Data from ...
Machine Learning Algorithms Humans Systems Biology Proteomics Metabolomics
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Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology Mar 5, 2021
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potenti...
Data Mining Ligands Molecular Targeted Therapy Host-Pathogen Interactions Metabolome Anti-Inflammatory Agents Humans Gastrointestinal Agents Machine Learning Signal Transduction Cells, Cultured Gastrointestinal Microbiome Metabolomics Gene Expression Profiling Transcriptome Protein Interaction Maps Bacteria Databases, Factual Inflammatory Bowel Diseases Drug Discovery
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