AIMC Topic: Databases, Genetic

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Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.

Frontiers in immunology
BACKGROUND: Low back pain resulting from intervertebral disc degeneration (IVDD) represents a significant global social problem. There are notable differences in the distribution of lymphatic vessels (LV) in normal and pathological intervertebral dis...

Integrative analysis and knowledgebase construction of key candidate genes and pathways in age-related macular degeneration.

Experimental eye research
Age-related macular degeneration is a retinal disease that severely impacts vision in the older population. Its gene-related heterogeneity has not been fully studied, increasing the burden of precise treatment, prevention and prognosis. Genetic varia...

Identification of immune-related mitochondrial metabolic disorder genes in septic shock using bioinformatics and machine learning.

Hereditas
PURPOSE: Mitochondria are involved in septic shock and inflammatory response syndrome, which severely affects the life security of patients. It is necessary to recognize and explore the immune-mitochondrial genes in septic shock.

GFPrint™: A machine learning tool for transforming genetic data into clinical insights.

PloS one
The increasing availability of massive genetic sequencing data in the clinical setting has triggered the need for appropriate tools to help fully exploit the wealth of information these data possess. GFPrint™ is a proprietary streaming algorithm desi...

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...

Potential diagnostic biomarkers in heart failure: Suppressed immune-associated genes identified by bioinformatic analysis and machine learning.

European journal of pharmacology
Heart failure (HF) threatens tens of millions of people's health worldwide, which is the terminal stage in the development of majority cardiovascular diseases. Recently, an increasing number of studies have demonstrated that bioinformatics and machin...

Comprehensive Analysis of Immune Infiltration and Key Genes in Peri-Implantitis Using Bioinformatics and Molecular Biology Approaches.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Peri-implantitis is the main cause of failure of implant treatment, and there is little research on its molecular mechanism. This study aimed to identify key biomarkers and immune infiltration of peri-implantitis using a bioinformatics met...

SFWN: A Novel Semi-Supervised Feature Weighted Neural Network for Gene Data Feature Learning and Mining With Graph Modeling.

IEEE journal of biomedical and health informatics
Gene expression data can serve for analyzing the genes with changed expressions, the correlation between genes and the influence of different circumstance on gene activities. However, labeling a large number of gene expression data is laborious and t...