Genomics & AI
We combine large-scale genomic data with artificial intelligence (AI) to identify genetic variants linked to Alzheimer’s disease. By using machine learning techniques, we can analyze vast datasets to find key genetic markers, helping us identify individuals at higher risk more accurately.
Selected Publications
- LD-informed deep learning for Alzheimer's gene loci detection using WGS data (Taeho Jo et al., 2023) LD-aware deep learning approach for AD gene loci discovery. [LINK]
- Deep learning–based genome-wide association analysis in Alzheimer’s disease (Presenting Author: Taeho Jo, AAIC 2021) Used a CNN on 12+ million SNPs for AD classification. [LINK]
- Deep learning-based identification of genetic variants (Taeho Jo et al., Briefings in Bioinformatics, 2022) SWAT-CNN approach, achieving AUC of 0.82. [LINK]
- Deep Learning-based SWAT-Tab Approach for Identifying Genetic Variants using Whole Genome Sequencing (Presenting Author: Taeho Jo, AAIC 2023) SWAT-TAB method on ADSP WGS data with improved efficiency. [LINK]