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Metabolomics

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From Microcosm to Macrocosm: The -Omics, Multiomics, and Sportomics Approaches in Exercise and Sports.

Omics : a journal of integrative biology
This article explores the progressive integration of -omics methods, including genomics, metabolomics, and proteomics, into sports research, highlighting the development of the concept of "sportomics." We discuss how sportomics can be used to compreh...

Untargeted metabolomic profiling in children identifies novel pathways in asthma and atopy.

The Journal of allergy and clinical immunology
BACKGROUND: Asthma and other atopic disorders can present with varying clinical phenotypes marked by differential metabolomic manifestations and enriched biological pathways.

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a vital problem in contemporary medicine. Numerous algorithms, many of which were derived with the aid of artificial intelligence, were brought up in a...

Machine Learning and Omics Analysis in Aortic Aneurysm.

Angiology
Aortic aneurysm is a life-threatening condition and mechanisms underlying its formation and progression are still incompletely understood. Omics approach has brought new insights to identify a broad spectrum of biomarkers and better understand cellul...

Recent methodological advances towards single-cell proteomics.

Proceedings of the Japan Academy. Series B, Physical and biological sciences
Studying the central dogma at the single-cell level has gained increasing attention to reveal hidden cell lineages and functions that cannot be studied using traditional bulk analyses. Nonetheless, most single-cell studies exploiting genomic and tran...

Urine and serum metabolic profiling combined with machine learning for autoimmune disease discrimination and classification.

Chemical communications (Cambridge, England)
Precision diagnosis and classification of autoimmune diseases (ADs) is challenging due to the obscure symptoms and pathological causes. Biofluid metabolic analysis has the potential for disease screening, in which high throughput, rapid analysis and ...

Highly automatic and universal approach for pure ion chromatogram construction from liquid chromatography-mass spectrometry data using deep learning.

Journal of chromatography. A
Feature extraction is the most fundamental step when analyzing liquid chromatography-mass spectrometry (LC-MS) datasets. However, traditional methods require optimal parameter selections and re-optimization for different datasets, thus hindering effi...

Combined mechanistic modeling and machine-learning approaches in systems biology - A systematic literature review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Mechanistic-based Model simulations (MM) are an effective approach commonly employed, for research and learning purposes, to better investigate and understand the inherent behavior of biological systems. Recent advancements ...

PeakDetective: A Semisupervised Deep Learning-Based Approach for Peak Curation in Untargeted Metabolomics.

Analytical chemistry
Peak-detection algorithms currently used to process untargeted metabolomics data were designed to maximize sensitivity at the sacrifice of selectively. Peak lists returned by conventional software tools therefore contain a high density of artifacts t...

OSCA-finder: Redefining the assay of kidney disease diagnostic through metabolomics and deep learning.

Talanta
Liquid chromatography-mass spectrometry (LC-MS) is a platform for urine and blood sample analysis. However, the high variability in the urine sample reduced the confidence of metabolite identification. Therefore, pre and post-calibration operations a...