AIMC Topic: Databases, Genetic
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Integrating machine learning, bioinformatics and experimental verification to identify a novel prognostic marker associated with tumor immune microenvironment in head and neck squamous carcinoma.
Frontiers in immunology
Dec 10, 2024
Head and neck squamous carcinoma (HNSC), characterized by a high degree of malignancy, develops in close association with the tumor immune microenvironment (TIME). Therefore, identifying effective targets related to HNSC and TIME is of paramount impo...
KGRACDA: A Model Based on Knowledge Graph from Recursion and Attention Aggregation for CircRNA-Disease Association Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
CircRNA is closely related to human disease, so it is important to predict circRNA-disease association (CDA). However, the traditional biological detection methods have high difficulty and low accuracy, and computational methods represented by deep l...
MDMNI-DGD: A novel graph neural network approach for druggable gene discovery based on the integration of multi-omics data and the multi-view network.
Computers in biology and medicine
Dec 6, 2024
Accurately predicting druggable genes is of paramount importance for enhancing the efficacy of targeted therapies, reducing drug-related toxicities and improving patients' survival rates. Nevertheless, accurately predicting candidate cancer-druggable...
Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.
Frontiers in immunology
Dec 4, 2024
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
Nov 28, 2024
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
Nov 28, 2024
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
Nov 27, 2024
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
Nov 25, 2024
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
Nov 23, 2024
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...
The diagnostic value investigation of programmed cell death genes in heart failure.
BMC cardiovascular disorders
Nov 22, 2024
BACKGROUND: We aimed to identify the potential diagnostic markers and associated molecular mechanisms based on programmed cell death (PCD)-related genes in patients with heart failure (HF).
Humans
Transcriptome
Case-Control Studies
Protein Interaction Maps
Gene Regulatory Networks
Machine Learning
Reproducibility of Results
Gene Expression Profiling
Plasminogen Activator Inhibitor 1
Gene Expression Regulation
Apoptosis Regulatory Proteins
Predictive Value of Tests
Genetic Markers
Heart Failure
Nomograms
Databases, Genetic
Apoptosis
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