AIMC Topic: Polymorphism, Single Nucleotide

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SyMetrics: an integrated machine learning model for evaluating the pathogenicity of synonymous variants in the human genome.

NAR genomics and bioinformatics
Synonymous single nucleotide variants (sSNVs), traditionally seen as neutral, are now recognized for their biological impact. To assess their relevance, we developed SyMetrics, a framework that integrates predictors of splicing, RNA stability, evolut...

GermVersity: A free and user-friendly interface to enhance the visualization and analysis of genebank data.

PloS one
Genebanks are crucial for food security and industrial applications. However, their heterogeneous nature hinders effective utilization. To address this, the GermVersity platform was developed to integrate conventional, artificial intelligence, and da...

Bayesian neural networks for genomic prediction: uncertainty quantification and SNP interpretation with SHAP and GWAS.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
This study presents a Bayesian neural networks framework with LASSO regularization and the GSMeSP interpretability tool, enabling accurate, uncertainty-aware, and biologically interpretable genomic prediction. Deep learning offers significant potenti...

Genome-wide association study reveals genetic architecture and evolution of human retinal pigmentation.

Science advances
Pigmentation varies widely across humans and is shaped by melanin quantity, type, and spatial distribution. Retinal pigmentation protects against light-induced damage, yet its genetic and evolutionary bases remain unclear. We developed a deep learnin...

Decoding the germline genetic architecture of prostate cancer at a single cell resolution.

PLoS genetics
Prostate cancer exhibits a strong familial association, and its heritability indicates a significant contribution from germline variants. While genome-wide association studies (GWAS) have identified common germline variants associated with prostate c...

Candidate genes for anthracnose resistance in Senegalese sorghum: a machine learning-based exploration.

Functional & integrative genomics
Anthracnose, caused by the hemibiotrophic fungal pathogen Colletotrichum sublineola, is a significant constraint to sorghum production worldwide. Developing resistant cultivars is the most sustainable control strategy, but it requires constant additi...

Transformer-based deep learning enhances discovery in migraine GWAS.

Nature communications
Migraine is a complex neurological disorder with substantial heritability, yet genome-wide association studies (GWAS) have explained only a fraction of its genetic component. We developed InsightGWAS, a Transformer-based model, to enhance genetic dis...

The - 216G/T polymorphism in the EGFR gene: A review focusing on Non-Small lung cancer.

Molecular biology reports
The epidermal growth factor receptor (EGFR) is a key regulator of cell proliferation and a well-established therapeutic target in non-small-cell lung cancer (NSCLC). Somatic mutations in the EGFR gene have been widely studied in the context of tyrosi...

An Improved Deep Semi-supervised JNMF Method for Biomarker Extraction of Alzheimer's Disease.

Journal of molecular neuroscience : MN
Imaging genetics is an approach that explores the underlying mechanisms of brain disorders such as Alzheimer's disease (AD) by analyzing the correlation between neuroimaging and genetic data. Traditional non-negative matrix factorization (NMF) algori...

ML-MAGES enables multivariate genetic association analyses with genes and effect size shrinkage.

Genome research
A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges account for inflation in GWA ...