Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions

Abstract: Molecular simulations informed by experimental data can provide detailed knowledge of complex biomolecular structure. However, it is a challenging task to weight experimental information with respect to the underlying model. A self-adapting type of dynamic particle swarm optimization can tackle the parameter selection problem, which is demonstrated on small-angle X-ray scattering-guided protein simulations.
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