Yiheng Zhu

This paper introduces ProtET, a method for CLIP-informed protein editing using multi-modality learning, achieving significant improvements in protein stability and functionality.

ULDNA improves DNA-binding site prediction using a LSTM-attention network with pre-trained language models, achieving higher accuracy than existing methods on 1287 proteins.

The paper introduces ATGO, a deep-learning method that improves Gene Ontology prediction for proteins using self-attention transformers and triplet networks, achieving higher accuracy than existing methods.

TripletGO improves gene function annotations by integrating transcript expression, sequence alignment, and probability models across multiple species and proteins.