Switch Laboratory, VIB Center for Brain and Disease Research, VIB, Leuven 3000, Belgium.
Switch Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Leuven 3000, Belgium.
Bioinformatics. 2024 Mar 29;40(4). doi: 10.1093/bioinformatics/btae160.
Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation.
We present MadraX, a forcefield implemented as a differentiable PyTorch module, able to interact with deep learning algorithms in an end-to-end fashion.
MadraX documentation, together with tutorials and installation guide, is available at madrax.readthedocs.io.
当可用数据有限时，应用于结构生物学的深度学习算法往往难以收敛到有意义的解决方案，因为它们需要从示例中学习复杂的物理规则。然而，由于其实现方式，最先进的力场无法与深度学习算法接口。
我们提出了 MadraX，这是一个实现为可微分 PyTorch 模块的力场，能够以端到端的方式与深度学习算法交互。
MadraX 的文档，以及教程和安装指南，可在 madrax.readthedocs.io 上获得。
