AIMC Topic: Genetic Variation
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Prediction of human pathogenic start loss variants based on self-supervised contrastive learning.
BMC biology
Aug 8, 2025
BACKGROUND: Start loss variants are a class of genetic variants that affect the bases of the start codon, disrupting the normal translation initiation process and leading to protein deletions or the production of different proteins. Accurate assessme...
Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds.
BMC genomics
Aug 8, 2025
BACKGROUND: Shandong's local duck breeds are renowned for their outstanding egg-laying performance and are regarded as valuable assets within China's waterfowl germplasm. Understanding the genetic characteristics of these populations, along with moni...
varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction.
Genome medicine
Aug 4, 2025
BACKGROUND: Machine learning and artificial intelligence are increasingly being applied to identify phenotypically causal genetic variation. These data-driven methods require comprehensive training sets to deliver reliable results. However, large unb...
In silico prediction of variant effects: promises and limitations for precision plant breeding.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Jul 28, 2025
Sequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies. Plant breeding has traditionally relied on ph...
Lineage-specific regulatory evolution: insights from massively parallel reporter assays.
Current opinion in genetics & development
Jun 20, 2025
Lineage-specific genetic variants play a key role in evolutionary divergence, particularly through changes in cis-regulatory elements that fine-tune gene expression. Massively parallel reporter assays (MPRAs) provide a powerful approach to characteri...
Single-cell data combined with phenotypes improves variant interpretation.
BMC genomics
May 28, 2025
BACKGROUND: Whole genome sequencing offers significant potential to improve the diagnosis and treatment of rare diseases by enabling the identification of thousands of rare, potentially pathogenic variants. Existing variant prioritisation tools can b...
Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.
Genome research
May 2, 2025
Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F crosses with extensive genetic diversity...
Harnessing genotype and phenotype data for population-scale variant classification using large language models and bayesian inference.
Human genetics
Apr 23, 2025
Variants of Uncertain Significance (VUS) in genetic testing for hereditary diseases burden patients and clinicians, yet clinical data that could reduce VUS are underutilized due to a lack of scalable strategies. We assessed whether a machine learning...
DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants.
BMC bioinformatics
Apr 9, 2025
BACKGROUND: A significant challenge in precision medicine is confidently identifying mutations detected in sequencing processes that play roles in disease treatment or diagnosis. Furthermore, the lack of representativeness of single nucleotide varian...
Common genetic variants do not impact clinical prediction of methotrexate treatment outcomes in early rheumatoid arthritis.
Journal of internal medicine
Apr 6, 2025
BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to predict. The role of genetics remains unclear, but studies suggest its importance.
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