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Innovative methods for investigating the genetic architecture of complex human traits
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Novel Machine Learning Methods for Genomic Data Analysis
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Association Study between Diseases and Human Tissue-Specific Epigenomes
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Developing enrichment analyzing methods at sub-cell type level to generate novel insights on complex disease pathogenesis
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Statistical Methods for Analyzing Microbiome Data
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Disease Risk annotation of Genomic and Epigenomic Variants using Machine Learning Approaches
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Characterizing the Developmental Trajectories for Cerebellar Volumes via Penalized Splines and Derivative Analysis
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EDClust: An EM-MM hybrid method for cell clustering in population-level single cell RNA sequencing
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Applying Genome-Wide Association Study to Analyze Novel Variants That Potentially Relate to Alzheimer’s Disease
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Stability of Inference Derived from Machine Learning-based Doubly Robust Estimators of Treatment Effects
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