Taedong Yun

This paper introduces a deep learning framework, REGLE, that improves genomic discovery and risk prediction for respiratory and circulatory diseases by learning low-dimensional embeddings from high-dimensional clinical data.

This paper introduces M-REGLE, a multimodal deep learning method that improves genetic analysis of cardiovascular traits by integrating multiple clinical data modalities and outperforms unimodal approaches in locus discovery and risk prediction.

DeepConsensus improves PacBio HiFi read accuracy and assembly quality using a gap-aware transformer model.

DeepTrio improves variant calling in family trios using deep learning, achieving higher accuracy than DeepVariant, especially at lower coverages.

This study improves variant calling by integrating population data into deep learning models, enhancing precision and recall across diverse populations.

The paper introduces a scalable variant-calling method using DeepVariant and GLnexus, achieving improved quality and cost savings over existing practices.