Jianbo Qiao

The paper shows DNA sequence determines the destination of spontaneous epimutations in plants, using a deep-learning model trained on one methylome to predict methylation set points across species.

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.

The paper introduces RiboSeek, a framework for RNA 3D structure search using geometric alphabets, achieving fast and accurate comparisons.

MultiNano uses multi-view deep learning to accurately detect and quantify m6A RNA modifications from Nanopore DRS signals, achieving state-of-the-art performance in multiple tasks.

HGCPep improves ncPEP identification by using a hypergraph model to capture peptide-RNA relationships, outperforming existing methods.