AIMC Topic: Metabolomics
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Metabolomic Plasma Profile of Chronic Obstructive Pulmonary Disease Patients.
International journal of molecular sciences
May 9, 2025
The analysis of blood metabolites may help identify individuals at risk of having COPD and offer insights into its underlying pathophysiology. This study aimed to identify COPD-related metabolic alterations and generate a biological signature potenti...
Metabolomic profiles underlying gout flares: a prospective study of people with gout.
RMD open
May 8, 2025
OBJECTIVES: To identify specific metabolomic profiles associated with gout flares in people with gout.
Predicting Sprint Potential: A Machine Learning Model Based on Blood Metabolite Profiles in Young Male Athletes.
European journal of sport science
Mar 1, 2025
This study aims to utilize male blood metabolite signatures for (i) distinguishing between healthy individuals and athletes, thereby optimizing the athlete screening process; and (ii) predicting athletic performance in 100, 200, and 400 m sprints, en...
Machine learning and metabolomics identify biomarkers associated with the disease extent of ulcerative colitis.
Journal of Crohn's & colitis
Feb 4, 2025
BACKGROUND AND AIMS: Ulcerative colitis (UC) is a metabolism-related chronic intestinal inflammatory disease. Disease extent is a key parameter of UC. Using serum metabolic profiling to identify noninvasive biomarkers of disease extent may inform the...
AI-driven multi-omics profiling of sepsis immunity in the digestive system.
Frontiers in immunology
Jan 1, 2025
Sepsis is a life-threatening systemic inflammatory syndrome characterized by a complex immune biphasic imbalance. Monitoring of immune status has not yet been implemented in clinical practice due to lack of direct therapeutic utility. Immune dysregul...
Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.
Translational vision science & technology
Dec 2, 2024
PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, develop risk models to differentiate diabetic macular edema (DME), and predict anti-vascular endothelial growth factor (anti-VEGF) therapy response.
Development of a Serum Metabolome-Based Test for Early-Stage Detection of Multiple Cancers.
Cancer reports (Hoboken, N.J.)
Nov 1, 2024
BACKGROUND: Detection of cancer at the early stage currently offers the only viable strategy for reducing disease-related morbidity and mortality. Various approaches for multi-cancer early detection are being explored, which largely rely on capturing...
Machine learning-based clustering identifies obesity subgroups with differential multi-omics profiles and metabolic patterns.
Obesity (Silver Spring, Md.)
Nov 1, 2024
OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct ca...
A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology.
Briefings in functional genomics
Sep 27, 2024
Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biological interaction between different omics. Machine learning approaches have been extensively employed in this context over the years. This review aims t...
An Ensemble Spectral Prediction (ESP) model for metabolite annotation.
Bioinformatics (Oxford, England)
Aug 2, 2024
MOTIVATION: A key challenge in metabolomics is annotating measured spectra from a biological sample with chemical identities. Currently, only a small fraction of measurements can be assigned identities. Two complementary computational approaches have...
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