AIMC Topic: Polymorphism, Single Nucleotide
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Neur-Ally: a deep learning model for regulatory variant prediction based on genomic and epigenomic features in brain and its validation in certain neurological disorders.
NAR genomics and bioinformatics
Jun 13, 2025
Large-scale quantitative studies have identified significant genetic associations for various neurological disorders. Expression quantitative trait locus (eQTL) studies have shown the effect of single-nucleotide polymorphisms (SNPs) on the differenti...
Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.
PloS one
Jun 6, 2025
Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct human-caused historical long-distance seed transfer and to spot mislabelling in forest field trials....
Case-control study combined with machine learning techniques to identify key genetic variations in GSK3B that affect susceptibility to diabetic kidney diseases.
BMC endocrine disorders
Jun 5, 2025
The role of genetic susceptibility in early warning and precise treatment of diabetic kidney disease (DKD) requires further investigation. A case-control study was conducted to evaluate the predictive effect of GSK3B genetic polymorphisms on the susc...
Screening of glioma susceptibility SNPs and construction of risk models based on machine learning algorithms.
BMC neurology
Jun 5, 2025
BACKGROUND: Glioma is a common primary malignant brain tumor. This study aimed to develop a predictive model for glioma risk by these screened key SNPs in the Chinese Han population.
Detecting genetic interactions with visible neural networks.
Communications biology
Jun 5, 2025
Non-linear interactions among single nucleotide polymorphisms (SNPs), genes, and pathways play an important role in human diseases, but identifying these interactions is a challenging task. Neural networks are state-of-the-art predictors in many doma...
Performance of deep-learning-based approaches to improve polygenic scores.
Nature communications
Jun 2, 2025
Polygenic scores, which estimate an individual's genetic propensity for a disease or trait, have the potential to become part of genomic healthcare. Neural-network based deep-learning has emerged as a method of intense interest to model complex, nonl...
Prediction of Lymph Node Metastasis in Non-Small Cell Lung Carcinoma Using Primary Tumor Somatic Mutation Data.
JCO clinical cancer informatics
May 30, 2025
PURPOSE: Lymph node metastasis (LNM) significantly affects prognosis and treatment strategies in non-small cell lung cancer (NSCLC). Current diagnostic methods, including imaging and histopathology, have limited sensitivity and specificity. This stud...
PRP: pathogenic risk prediction for rare nonsynonymous single nucleotide variants.
Human genetics
May 29, 2025
Reliable prediction of pathogenic variants plays a crucial role in personalized medicine, which aims to provide accurate diagnosis and individualized treatment using genomic medicine. This study introduces PRP, a pathogenic risk prediction for rare n...
Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci.
Scientific reports
May 2, 2025
To compare the comprehensive performance of conventional logistic regression (LR) and seven machine learning (ML) algorithms in Noise-Induced Hearing Loss (NIHL) prediction, and to investigate the single nucleotide polymorphism (SNP) loci significant...
Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.
IEEE transactions on neural networks and learning systems
May 2, 2025
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the impo...
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