Early and accurate diagnosis significantly improves the chances of disease survival. DNA methylation (5mC), the major DNA modification in the human genome, is now recognized as a biomarker of immense clinical potential. This is due to its ability to ...
Hae Kyung Im's research group focuses on quantitative computational and statistical methods to tackle genomic data analysis and provides methods to translate the vast amount of genomic data for health research. In collaboration with Mengjie Chen's gr...
Transcriptome-wide association studies (TWASs) help identify disease-causing genes but often fail to pinpoint disease mechanisms at the cellular level because of the limited sample sizes and sparsity of cell-type-specific expression data. Here, we pr...
Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early lesions. Noninvasive biomarkers are urgently needed for early diagnosis and personalized treatment. Th...
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 ...
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...
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...
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 ...
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-...
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...
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