Chenjie Feng

AlphaVariant uses reinforcement learning with evolutionary priors to optimize enzyme variants from sparse experimental data, achieving high activity improvements in multiple rounds of optimization.

ProteinMCP accelerates and democratizes protein engineering by automating workflows and integrating 38 tools, achieving a comprehensive fitness modeling task in 11 minutes.

DRfold2 improves RNA structure prediction using a composite language model and denoising module, outperforming existing methods in contact prediction and complementing AlphaFold3.

PGAR-Zernike provides a fast and accurate open-source toolkit for computing Zernike descriptors of protein structures, enabling efficient structural database construction and retrieval.

This paper introduces DRfold, a method that improves RNA tertiary structure prediction by integrating deep learning with geometric potentials, achieving significant performance gains over existing methods.

This paper introduces trRosettaRNA, a deep learning method for RNA 3D structure prediction, showing improved accuracy over existing methods on benchmark datasets.