AIMC Topic: Genetic Variation

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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...
Phenotype Gene Expression Profiling Single-Cell Analysis Humans Genetic Variation
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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...
Embryonic Development Drosophila Proteins Drosophila melanogaster Transcription Factors Alleles Genetic Variation Binding Sites Drosophila Animals Deep Learning Protein Binding
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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...
Bayes Theorem Phenotype Genetic Testing Language Genetic Variation Genotype Humans Large Language Models Machine Learning
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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...
Decision Trees Mutation Genetic Variation Software Algorithms Genomics Humans Machine Learning
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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.
Male Middle Aged Arthritis, Rheumatoid Sweden Aged Adult Methotrexate Humans Genetic Variation Genotype Female Antirheumatic Agents Treatment Outcome Registries
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Assessment for antibiotic resistance in : A practical and interpretable machine learning model based on genome-wide genetic variation.

Virulence Mar 21, 2025
() antibiotic resistance poses a global health threat. Accurate identification of antibiotic resistant strains is essential for the control of infection. In the present study, our goal is to leverage the whole-genome data of to develop practical an...
Drug Resistance, Bacterial Microbial Sensitivity Tests Drug Resistance, Multiple, Bacterial Polymorphism, Single Nucleotide Computational Biology Helicobacter pylori Humans Helicobacter Infections Genetic Variation Machine Learning Genome, Bacterial Anti-Bacterial Agents
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Improving genetic variant identification for quantitative traits using ensemble learning-based approaches.

BMC genomics Mar 12, 2025
BACKGROUND: Genome-wide association studies (GWAS) are rapidly advancing due to the improved resolution and completeness provided by Telomere-to-Telomere (T2T) and pangenome assemblies. While recent advancements in GWAS methods have primarily focused...
Genome-Wide Association Study Polymorphism, Single Nucleotide Humans Genetic Variation Quantitative Trait Loci Machine Learning Phenotype Ensemble Learning Quantitative Trait, Heritable
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Applying artificial intelligence to uncover the genetic landscape of coagulation factors.

Journal of thrombosis and haemostasis : JTH Jan 9, 2025
Artificial intelligence (AI) is rapidly advancing our ability to identify and interpret genetic variants associated with coagulation factor deficiencies. This review introduces AI, with a specific focus on machine learning (ML) methods, and examines ...
Genetic Variation Humans Artificial Intelligence Blood Coagulation Factors Hemophilia A Genetic Association Studies Blood Coagulation Machine Learning Mutation Phenotype Genetic Predisposition to Disease
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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...
Macular Degeneration Polymorphism, Single Nucleotide Humans Knowledge Bases Databases, Genetic Genetic Variation Genetic Predisposition to Disease Vascular Endothelial Growth Factor A
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Toward trustable use of machine learning models of variant effects in the clinic.

American journal of human genetics Nov 18, 2024
There has been considerable progress in building models to predict the effect of missense substitutions in protein-coding genes, fueled in large part by progress in applying deep learning methods to sequence data. These models have the potential to e...
Mutation, Missense Deep Learning Models, Genetic Genetic Variation Humans Machine Learning Computer Simulation
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