AIMC Topic: Gene Expression Profiling

Clear Filters Showing 571 to 580 of 1601 articles

Machine Learning Integration with Single-Cell Transcriptome Sequencing Datasets Reveals the Impact of Tumor-Associated Neutrophils on the Immune Microenvironment and Immunotherapy Outcomes in Gastric Cancer.

International journal of molecular sciences
The characteristics of neutrophils play a crucial role in defining the tumor inflammatory environment. However, the function of tumor-associated neutrophils (TANs) in tumor immunity and their response to immune checkpoint inhibitors (ICIs) remains in...

XModNN: Explainable Modular Neural Network to Identify Clinical Parameters and Disease Biomarkers in Transcriptomic Datasets.

Biomolecules
The Explainable Modular Neural Network (XModNN) enables the identification of biomarkers, facilitating the classification of diseases and clinical parameters in transcriptomic datasets. The modules within XModNN represent specific pathways or genes o...

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to fatty acid metabolism-associated genes.

Scientific reports
Sepsis, characterized as a systemic inflammatory response triggered by the invasion of pathogens, represents a continuum that may escalate from mild systemic infection to severe sepsis, potentially resulting in septic shock and multiple organ dysfunc...

Machine learning based anoikis signature predicts personalized treatment strategy of breast cancer.

Frontiers in immunology
BACKGROUND: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the urgent need for innovative prognostic tools to improve treatment strategies. Anoikis, a form of programmed cell death critical in preventing metasta...

A multi-class support vector machine classification model based on 14 microRNAs for forensic body fluid identification.

Forensic science international. Genetics
MicroRNAs (miRNAs) are promising biomarkers for forensic body fluid identification owing to their small size, stability against degradation, and differential expression patterns. However, the expression of most body fluid-miRNAs is relative (differen...

Analysis of the relationships between interferon-stimulated genes and anti-SSA/Ro 60 antibodies in primary Sjögren's syndrome patients via multiomics and machine learning methods.

International immunopharmacology
BACKGROUND: Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease characterized by lymphocyte infiltration of the exocrine glands. Interferon-stimulated genes (ISGs) are often upregulated in patients with pSS, and anti-SSA/Ro 60 a...

Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.

International journal of molecular sciences
In oncology, there is a critical need for robust biomarkers that can be easily translated into the clinic. We introduce a novel approach using paired differential gene expression analysis for biological feature selection in machine learning models, e...

A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.

Cells
The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been develo...

SDC4 protein action and related key genes in nonhealing diabetic foot ulcers based on bioinformatics analysis and machine learning.

International journal of biological macromolecules
Diabetic foot ulcers (DFU) is a complication associated with diabetes characterised by high morbidity, disability, and mortality, involving chronic inflammation and infiltration of multiple immune cells. We aimed to identify the critical genes in non...