Kevin Yang

This paper introduces TrASPr+BOS, a generative AI model for predicting and designing RNA to achieve tissue-specific splicing outcomes, showing improved performance over existing methods.

The paper identifies sequence features associated with recursive splicing and develops a classifier to detect these features.

The paper improves sQTL modeling by incorporating alternative splicing representation and introduces MAJIQTL, finding new sQTLs linked to Alzheimer's disease.

This paper introduces LSV-seq, a targeted RNA-seq method optimized with machine learning to detect alternative splicing with high sensitivity and low sequencing depth.