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MetabolomicsTargeted metabolomic profiling and machine learning-based prediction models for persistent atrial fibrillation: a multi-center observational study

Background. Atrial fibrillation (AF), the most common cardiac arrhythmia worldwide, carries a high risk of severe complications. Patients diagnosed with paroxysmal atrial fibrillation (PAF) may progress to persistent atrial fibrillation (PerAF) following a period. We aimed to identify metabo...

2026-07-03 | MTBLS13136 | MetaboLights
MetabolomicsEmploying fingerprinting of medicinal plants by means of LC-MS and machine learning for species identification task

A dataset of liquid chromatography-mass spectrometry measurements of medicinal plant extracts from 76 species was generated and used for training and validating plant species identification algorithms. Various strategies for data handling and feature space selection were tested. Constrained Tucke...

2022-04-15 | MTBLS688 | MetaboLights
MetabolomicsDifferential Metabolomic Biomarkers Analysis of Apheresis Platelet Storage Based on Machine Learning Models

Platelet storage lesion (PSL) is a critical factor limiting the efficacy of platelet transfusion. Although hypothermic (4°C) storage is considered beneficial for maintaining platelet function, the underlying mechanisms of systemic metabolic reprogramming remain incompletely understood. This study...

2026-07-27 | MTBLS15165 | MetaboLights
MetabolomicsMetabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by oxaliplatin

Background: Oxaliplatin-induced peripheral neuropathy (OIPN) poses a significant challenge for patients with colorectal tumor, often resulting in treatment interruption or discontinuation and subsequent treatment failure. Herein, a longitudinal untargeted metabolomic study to reveal the metabolom...

2025-08-14 | MTBLS12854 | MetaboLights
Metabolomics1H NMR-Based Plasma Metabolomics and Machine Learning Reveal Distinct Metabolic Signatures of Breast Cancer in Nigerian Women

Metabolic dysregulation is a hallmark of cancer and provides insights into biomarker discovery. Untargeted 1H NMR metabolomics offers a non-invasive means to identify biomarkers in breast cancer (BC) patients; however, metabolic signatures specific to Nigerian women remain poorly understood. This...

2026-02-23 | MTBLS13829 | MetaboLights
ProteomicsFast and accurate bacterial species identification in biological samples using LC-MS/MS mass spectrometry and machine learning (DIA dataset)
We have developed a new strategy for identifying bacterial species in biological samples using specific LC-MS/MS peptidic signatures. In the first training step, deep proteome coverage of bacteria of interest is obtained in Data Independent Acquisition (DIA) mode, followed by the use of machine lear...
ORGANISM(S): Citrobacter Freundii (ncbitaxon:546) Streptococcus Agalactiae 2603v/r (ncbitaxon:208435) Staphylococcus Aureus Subsp. Aureus Nctc 8325 (ncbitaxon:93061) Streptococcus Mitis (ncbitaxon:28037) Klebsiella Oxytoca (ncbitaxon:571) Staphylococcus Epidermidis Atcc 12228 (ncbitaxon:176280) Enterococcus Faecalis V583 (ncbitaxon:226185) Enterobacter Aerogenes Kctc 2190 (ncbitaxon:1028307) Proteus Mirabilis (ncbitaxon:584) Escherichia Coli K-12 (ncbitaxon:83333) Enterobacter Cloacae (ncbitaxon:550) Klebsiella Pneumoniae Subsp. Pneumoniae Mgh 78578 (ncbitaxon:272620) Pseudomonas Aeruginosa Pao1 (ncbitaxon:208964) Staphylococcus Saprophyticus Subsp. Saprophyticus Atcc 15305 (ncbitaxon:342451) Staphylococcus Haemolyticus Jcsc1435 (ncbitaxon:279808) 
2019-05-16 | MSV000083793 | MassIVE
ProteomicsPeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements
Global proteomics datasets to study ash utilization by R. toruloides. PeakDecoder is a workflow for metabolite identification and accurate profiling in multidimensional LC-IM-MS-DIA measurements. It is available at https://github.com/EMSL-Computing/PeakDecoder
ORGANISM(S): Rhodosporidium Toruloides Np11 (ncbitaxon:1130832) 
2023-02-03 | MSV000091202 | MassIVE
ProteomicsPeptideForest: Semi-supervised machine learning integrating multiple search engines for peptide identification
We introduce PeptideForest, a semi-supervised machine learning approach that integrates the assignment of peptides to mass spectra from multiple algorithms to train a random forest classifier, thereby combining the results from different search engines. PeptideForest increases the number of peptide-...
ORGANISM(S): Homo sapiens (Human) Escherichia coli 
2025-06-02 | PXD056915 | Pride
Human Machine learning E. coli Statistical post-processing Peptide identification 
ProteomicsUrinary Proteomic Spectra Analysis Based on Machine Learning for Classification of Kidney Diseases
To extract urinary proteome spectral features based on advanced mass spectrometer and machine learning algorithms, it could get more accurate reporting results for disease classification. We tried to establish a novel diagnosis model of kidney diseases by combining machine learning XGBoost algorithm...
ORGANISM(S): Homo sapiens (Human) 
2022-09-13 | PXD018996 | Pride
Kidney disease classification  urinary proteomics  machine learning algorithm  diagnosis 
ProteomicsPredictive Stool-Based Protein Biomarkers for the Classification of Crohn's Disease and Ulcerative Colitis Using a Machine Learning Approach
Background and Aim: Crohn's disease (CD) and ulcerative colitis (UC) are the two major chronic inflammatory bowel diseases (IBD). Although their symptoms are similar, their pathological features and clinical treatments differ. Currently, distinguishing between these diseases involves invasive proce...
ORGANISM(S): Homo sapiens (Human) 
2025-12-01 | PXD057120 | Pride
Crohn’s disease Inflammatory bowel disease (ibd) subtyping  protein biomarkers  dia mass spectrometry  quantitative proteomics  machine learning Ulcerative colitis. 
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