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MetabolomicsCoupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma

A discovery-based lipid profiling study of serum samples from a cohort that included patients with clear cell Renal Cell Carcinoma (ccRCC) stage I, II, III, and IV (n=112) and controls (n=52) was performed using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spec...

2020-11-20 | MTBLS1839 | MetaboLights
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
ProteomicsMachine Learning Based Classification of Diffuse Large B-cell Lymphoma Patients by their Protein Expression Profiles
Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we ...
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) 
2017-03-30 | MSV000080813 | MassIVE
ProteomicsDetection of SARS-CoV-2 in nasal swabs using MALDI-MS
Detection of SARS-CoV-2 using RT-PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs usin...
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) 
MSV000086175 | MassIVE
MetabolomicsIntegrative of Single-Cell RNA Sequencing and Metabolomics Decipher the Imbalanced Lipid-Metabolism in Maladaptive Immune Responses during Sepsis
To identify differentially expressed lipid metabolism-related genes (DE-LMRGs) responsible for immune dysfunction in sepsis. Machine learning algorithms were applied for screening hubgenes related to lipid metabolism. CIBERSORT and Single-sample GSEA were employed for assessing the immune cell infil...
2024-09-26 | MTBLS7315 | MetaboLights
ModelsAyush2018 - Breast Cancer Detection using SVM and WDBC Dataset
In this study, authors had briefly talked about the comparison of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) for binary classification of cancer. It is concluded that, SVMs perform better on cancer prediction which are not expressed by their genotype whereas ANNs capture the ...
2024-07-13 | MODEL2407130001 | BioModels
Machine Learning Model 
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 
ModelsLi2021 - HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors
The model predicts the inhibitory potential of small molecules against Histone deacetylase 3 (HDAC3), a relevant human target for cancer, inflammation, neurodegenerative diseases and diabetes. The authors have used a dataset of 1098 compounds from ChEMBL and validated the model using the benchmark M...
2024-08-06 | MODEL2406210001 | BioModels
Machine Learning Model FAIR-AIML Ersilia 
ModelsHuiyiLi2024 - Prediction of death risk in patients with acute diquat poisoning using Random Forest Model
The objective of this study was to develop and validate predictive models to assess the risk of death in patients with acute diquat (DQ) poisoning using innovative machine learning techniques. The study analyzed data from 201 consecutive patients admitted for deliberate oral intake of DQ between Feb...
2024-07-18 | MODEL2407180001 | BioModels
ProteomicsPrefrontal cortical synaptoproteome profile combined with machine learning predict resilience towards chronic social isolation in rats
Chronic social isolation (CSIS), an animal model of depression, generates two stress-response phenotypes: CSIS-resilient and CSIS-susceptible. However, the molecular mechanism underlying resilience to CSIS remains unclear. We aimed to investigate the prefrontal cortical synaptoproteome profile betwe...
ORGANISM(S): Rattus norvegicus (Rat) 
2024-04-23 | PXD047159 | Pride
Resilience Prefrontal cortex Proteomics Machine learning Chronic social isolation Synaptosome 
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