1 code implementation • 30 Oct 2024 • Yizhen Luo, Zikun Nie, Massimo Hong, Suyuan Zhao, Hao Zhou, Zaiqing Nie
To address these issues, we present MutaPLM, a unified framework for interpreting and navigating protein mutations with protein language models.
1 code implementation • 14 Jun 2024 • Yizhen Luo, Kai Yang, Massimo Hong, Xing Yi Liu, Zikun Nie, Hao Zhou, Zaiqing Nie
To address these issues, we present MV-Mol, a molecular representation learning model that harvests multi-view molecular expertise from chemical structures, unstructured knowledge from biomedical texts, and structured knowledge from knowledge graphs.
2 code implementations • 6 Jun 2023 • Yizhen Luo, Kai Yang, Massimo Hong, Xing Yi Liu, Zaiqing Nie
In this study, we introduce MolFM, a multimodal molecular foundation model designed to facilitate joint representation learning from molecular structures, biomedical texts, and knowledge graphs.
Ranked #10 on
Text-based de novo Molecule Generation
on ChEBI-20
no code implementations • 17 Apr 2023 • Yizhen Luo, Xing Yi Liu, Kai Yang, Kui Huang, Massimo Hong, Jiahuan Zhang, Yushuai Wu, Zaiqing Nie
In recent years, AI models that mine intrinsic patterns from molecular structures and protein sequences have shown promise in accelerating drug discovery.
no code implementations • 25 Feb 2022 • Niccolò Piazzesi, Massimo Hong, Andrea Ceccarelli
We show that adversarial attacks and faults injected in the trained agent can lead to erroneous decisions and severely jeopardize safety.