Di Wu

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.

This paper introduces a deep neural network-based two-part model for semi-continuous data and demonstrates its improved performance over existing methods.

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.