Yuhang Liu

This paper introduces LARK, a framework that learns chemical representations from reactions, showing improved performance in reaction prediction and molecular property prediction.

Melody predicts DNA methylation from genomic sequences across human tissues and outperforms existing methods, also generalizing to methylation quantitative trait locus effect prediction.

scMomer is a pretraining framework for single-cell multi-omics modeling under missing modality conditions, generating biologically meaningful embeddings and outperforming unimodal approaches in downstream tasks.

Super-delta2 is a differential expression analysis method for RNA-seq data that controls type I error and achieves high statistical power in multi-group comparisons.

iSeg is an efficient algorithm for genomic and epigenomic segmentation that uses dynamic programming and a novel data structure to identify and refine segments with statistical significance.