Yingfu Wu

SpatialClaw provides a memory-augmented system for spatial omics analysis, enabling end-to-end workflows through natural language interaction and outperforming standard models in benchmarking.

SpatialGEO improves identification of spatial regions in spatial transcriptomics data and reveals biological insights in tumor microenvironments and mouse development.

scHiCyclePred predicts cell cycle phases from single-cell Hi-C data using multi-scale interaction features, outperforming existing methods.

BERTE improves TE classification accuracy using BERT and CNN, achieving up to 21% higher F1-score than existing methods.

This paper introduces CREATE, a deep learning framework for TE classification, and WebDLTE, a web platform for real-time TE annotation, showing improved performance over existing tools.