Automatic forward model parameterization with Bayesian inference of conformational populations [0.03%]
基于贝叶斯推断构象群体的自动正向模型参数化
Robert M Raddi,Tim Marshall,Vincent A Voelz
Robert M Raddi
To quantify how well theoretical predictions of structural ensembles agree with experimental measurements, we depend on the accuracy of forward models (FMs). These models are computational frameworks that generate observable quantities from...
AutoSAS: A new human-aside-the-loop paradigm for automated SAS fitting for high throughput and autonomous experimentation [0.03%]
AutoSAS：一个新的无需人工干预的自动SAS拟合方法，适用于高通量和自主实验
Duncan R Sutherland,Rachel Ford,Yun Liu et al.
Duncan R Sutherland et al.
The advancement of artificial-intelligence driven autonomous experiments demands physics-based modeling and decision-making processes, not only to improve the accuracy of the experimental trajectory but also to increase trust by allowing tr...
Dreaming of electrical waves: Generative modeling of cardiac excitation waves using diffusion models [0.03%]
心律波的生成模型：使用扩散模型生成心脏兴奋波 снованные на моделировании диффузии
Tanish Baranwal,Jan Lebert,Jan Christoph
Tanish Baranwal
Electrical waves in the heart form rotating spiral or scroll waves during life-threatening arrhythmias, such as atrial or ventricular fibrillation. The wave dynamics are typically modeled using coupled partial differential equations, which ...