Haopeng Yu

PlantScience.ai couples an LLM-built, continuously updated plant science knowledge graph (4.0 million entities, 10.8 million edges) with graph-based retrieval for citation-traceable plant biology answers.

PlantRNA-FM is an interpretable RNA foundation model that improves RNA annotation and translation efficiency prediction in plants by identifying functional RNA motifs.

The paper introduces a machine learning tool, iM-Seeker, to predict DNA i-Motif folding status and strength using CUT&Tag data and biophysical experiments.

The paper reports the structure of AsCas12f1 and engineers it to enhance genome editing activity in human cells.

The paper identifies G-quadruplex structures in cold-adapted plants, showing they enhance mRNA stability and improve cold response.

RSVdb provides a database of transcriptome RNA structures from 8 species, enabling retrieval, visualization, prediction, and download of RNA structure data.

This study uses a deep neural network to predict in vivo mRNA structural stability by analyzing six features, finding ribosome density as the most influential factor.