AIMC Topic: Genome-Wide Association Study
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Rethinking GWAS: how lessons from genetic screens and artificial intelligence could reveal biological mechanisms.
Bioinformatics (Oxford, England)
Mar 29, 2025
MOTIVATION: Modern single-cell omics data are key to unraveling the complex mechanisms underlying risk for complex diseases revealed by genome-wide association studies (GWAS). Phenotypic screens in model organisms have several important parallels to ...
MIRACN: a residual convolutional neural network for predicting cell line specific functional regulatory variants.
Briefings in bioinformatics
Mar 4, 2025
In post-genome-wide association study era, interpretation of noncoding variants remains a significant challenge due to their complexity and the limited understanding of their functions. Here, we developed MIRACN, a novel residual convolutional neural...
MUTATE: a human genetic atlas of multiorgan artificial intelligence endophenotypes using genome-wide association summary statistics.
Briefings in bioinformatics
Mar 4, 2025
Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e. endophenotypes) that bridge the genetics and clinical manifestations of human disease. However, the genetic architecture of t...
Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).
The plant genome
Mar 1, 2025
Machine learning (ML) has garnered significant attention for its potential to enhance the accuracy of genomic predictions (GPs) in various economic crops with the use of complete genomic information. Genome-wide association studies (GWAS) are widely ...
scTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies.
Nucleic acids research
Jan 6, 2025
Single-cell transcriptome-wide association studies (scTWAS) is a new method for conducting TWAS analysis at the cellular level to identify gene-trait associations with higher precision. This approach helps overcome the challenge of interpreting cell-...
Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network.
PloS one
Jan 1, 2025
Genome-wide association studies (GWAS) have successfully uncovered numerous associations between genetic variants and disease traits to date. Yet, identifying significantly associated loci remains a considerable challenge due to the concomitant multi...
Identifying Common Diagnostic Biomarkers and Therapeutic Targets between COPD and Sepsis: A Bioinformatics and Machine Learning Approach.
International journal of chronic obstructive pulmonary disease
Jan 1, 2025
BACKGROUND: Evidence suggests a bidirectional association between chronic obstructive pulmonary disease (COPD) and sepsis, but the underlying mechanisms remain unclear. This study aimed to explore shared diagnostic genes, potential mechanisms, and th...
Machine Learning
Computational Biology
Molecular Docking Simulation
Biomarkers
Predictive Value of Tests
Gene Expression Profiling
Genome-Wide Association Study
Pulmonary Disease, Chronic Obstructive
Humans
Mendelian Randomization Analysis
Sepsis
Gene Regulatory Networks
Genetic Predisposition to Disease
[From AI to polygenic risk scores: which innovations will shape the future of psychiatry?].
Tijdschrift voor psychiatrie
Jan 1, 2025
BACKGROUND: In recent years, developments have been made in various research domains, from treatments with (es)ketamine to large-scale genome-wide association studies (GWAS).
Integrative Machine Learning of Glioma and Coronary Artery Disease Reveals Key Tumour Immunological Links.
Journal of cellular and molecular medicine
Jan 1, 2025
It is critical to appreciate the role of the tumour-associated microenvironment (TME) in developing strategies for the effective therapy of cancer, as it is an important factor that determines the evolution and treatment response of tumours. This wor...
Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bact...
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