2 citations · 4 across the 4 of their papers we have counts for
4 papers
Designing the Haystack: Programmable Chemical Space for Generative Molecular Discovery
Yuchen Zhu, Donghai Zhao, Yangyang Zhang +10
Chemical space exploration underlies drug discovery, yet most generative models treat chemical space as a fixed, implicitly learned distribution, focusing on sampling molecules rat…
BioScore: A Foundational Scoring Function For Diverse Biomolecular Complexes
Yuchen Zhu, Jihong Chen, Yitong Li +9
Structural assessment of biomolecular complexes is vital for translating molecular models into functional insights, shaping our understanding of biology and aiding drug discovery.…
Token-Mol 1.0: Tokenized drug design with large language model
Jike Wang, Rui Qin, Mingyang Wang +17
Significant interests have recently risen in leveraging sequence-based large language models (LLMs) for drug design. However, most current applications of LLMs in drug discovery la…
Human-level molecular optimization driven by mol-gene evolution
Jiebin Fang, Churu Mao, Yuchen Zhu +3
De novo molecule generation allows the search for more drug-like hits across a vast chemical space. However, lead optimization is still required, and the process of optimizing mole…