Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Sweden
- France
- Germany
- United Kingdom
- Denmark
- Portugal
- Poland
- Singapore
- Spain
- Czech
- Austria
- Italy
- Switzerland
- Belgium
- Luxembourg
- Norway
- Australia
- China
- Canada
- Finland
- Israel
- Japan
- Morocco
- Netherlands
- Vietnam
- Hong Kong
- Ireland
- Romania
- Slovenia
- United Arab Emirates
- Worldwide
- 22 more »
- « less
-
Program
-
Field
-
eliminate early signs of cancer. To try to understand the origin of this increased efficiency in mAb–CD16 binding, we have undertaken molecular dynamics calculations. The mission of the recruited researcher
-
of Biology includes a variety of faculty and over 350 undergraduate majors and Masters-level graduate students focusing on evolutionary, ecological, molecular, physiological, microbial, and health sciences
-
We strive to understand the central nervous system at multiple levels of function, from cells to cognition to social interactions. Our approaches range from molecular, cellular and experimental
-
properties of phase transitions involving magnetism, elasticity, dielectricity, etc. by applying and developing computational methods such as classical and quantum Monte Carlo simulations, molecular dynamics
-
research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
-
nanoparticles, cell survival and radioresistance. The MS-RADAM research programme combines state-of-the-artc omputational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics
-
study their structures and dynamics using multi-scale simulations, which include all-atom molecular dynamics (MD) simulations, coarse-grained MD simulations, quantum mechanics/molecular mechanics (QM/MM
-
: 10.1038/s41467-023-39181-2 Research area: Computational biophysics, drug delivery, protein design Keywords:Computer simulations, coarse-grained model, molecular dynamics, membrane fusion, fusion protein
-
molecular dynamics simulations across multiple resolutions, most likely from the atomistic to the coarse grained level, using a variety of force fields and computational methods. Run large-scale simulations
-
datasets across broad chemical space Evaluate models through molecular dynamics, simulations, and benchmarks Active Learning in Configurational and Chemical Spaces Integrate uncertainty-aware MLFFs