AIMC Topic: Genetic Variation
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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...
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...
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 ...
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...
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...
Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.
Molecular systems biology
Sep 16, 2024
Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissues and organs. However, variant effect prediction tools that aim to identify pathogenic variants are typically oblivious to tissue contexts. Here we r...
Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.
Food & function
Sep 16, 2024
Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molecular understanding of MI is elusive and needs to be fully explored. This study aimed to elucidate th...
The impacts of positive selection on genomic variation in Drosophila serrata: Insights from a deep learning approach.
Molecular ecology
Aug 26, 2024
This study explores the impact of positive selection on the genetic composition of a Drosophila serrata population in eastern Australia through a comprehensive analysis of 110 whole genome sequences. Utilizing an advanced deep learning algorithm (par...
Artificial intelligence in plant breeding.
Trends in genetics : TIG
Aug 7, 2024
Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scien...
Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance.
mSystems
Jul 2, 2024
UNLABELLED: The erythromycin resistance RNA methyltransferase () confers cross-resistance to all therapeutically important macrolides, lincosamides, and streptogramins (MLS phenotype). The expression of is often induced by the macrolide-mediated rib...
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