AIMC Topic: Genetic Predisposition to Disease
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Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank.
Nature genetics
Sep 11, 2024
The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, ...
A method for miRNA diffusion association prediction using machine learning decoding of multi-level heterogeneous graph Transformer encoded representations.
Scientific reports
Sep 3, 2024
MicroRNAs (miRNAs) are a key class of endogenous non-coding RNAs that play a pivotal role in regulating diseases. Accurately predicting the intricate relationships between miRNAs and diseases carries profound implications for disease diagnosis, treat...
TriFusion enables accurate prediction of miRNA-disease association by a tri-channel fusion neural network.
Communications biology
Aug 30, 2024
The identification of miRNA-disease associations is crucial for early disease prevention and treatment. However, it is still a computational challenge to accurately predict such associations due to improper information encoding. Previous methods char...
Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer's disease.
PLoS computational biology
Aug 26, 2024
Alzheimer's disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, and neuroinflammatory responses. Both resident microglia and peripheral immune cells have been associated with the immune component of AD. However, th...
Explore key genes of Crohn's disease based on glycerophospholipid metabolism: A comprehensive analysis Utilizing Mendelian Randomization, Multi-Omics integration, Machine Learning, and SHAP methodology.
International immunopharmacology
Aug 21, 2024
BACKGROUND AND AIMS: Crohn's disease (CD) is a chronic, complex inflammatory condition with increasing incidence and prevalence worldwide. However, the causes of CD remain incompletely understood. We identified CD-related metabolites, inflammatory fa...
Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk.
Lung cancer (Amsterdam, Netherlands)
Aug 9, 2024
OBJECTIVES: Lung Cancer (LC) is a multifactorial disease for which the role of genetic susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) to analyze differences between patients with LC based on family hi...
SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning.
Nature communications
Aug 5, 2024
Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputa...
An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.
PloS one
Jul 15, 2024
INTRODUCTION: Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so far been ...
Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?
Journal of the American Heart Association
Jun 15, 2024
BACKGROUND: Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to ass...
A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation.
BMC bioinformatics
Jun 14, 2024
BACKGROUND: The exploration of gene-disease associations is crucial for understanding the mechanisms underlying disease onset and progression, with significant implications for prevention and treatment strategies. Advances in high-throughput biotechn...
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