A5102723692- Topic Modeling
- Nanocluster Synthesis and Applications
- Machine Learning in Materials Science
- Protein Structure and Dynamics
- Advanced biosensing and bioanalysis techniques
- Cancer-related Molecular Pathways
École Polytechnique Fédérale de Lausanne
2025
Fudan University
2024
Most atomistic machine learning (ML) models rely on a locality ansatz and decompose the energy into sum of short-ranged, atom-centered contributions. This leads to clear limitations when trying describe problems that are dominated by long-range physical effects—most notably electrostatics. Many approaches have been proposed overcome these limitations, but efforts make them efficient widely available hampered need incorporate an ad hoc implementation methods treat interactions. We develop...
Intrinsically disordered proteins (IDPs) lack a well-defined tertiary structure but are essential players in various biological processes. Their ability to undergo disorder-to-order transition upon binding their partners, known as the folding-upon-binding process, is crucial for function. One classical example intrinsically transactivation domain (TAD) of tumor suppressor protein p53, which quickly forms structured α-helix after its partner MDM2, with clinical significance cancer treatment....