论文标题
分子模拟轨迹的时置T-分布的随机邻居嵌入（T-SNE）
Time-Lagged t-Distributed Stochastic Neighbor Embedding (t-SNE) of Molecular Simulation Trajectories
论文作者
论文摘要
分子模拟轨迹代表高维数据。可以通过降低维度的方法来可视化此类数据。由于原子的运动是非线性的，因此非线性降低降低方法可能比线性更有效。在这里，我们测试了一种流行的非线性T-分布随机邻居嵌入（T-SNE）方法，用于分析丙氨酸二肽动力学和TRP型盘折叠和展开的轨迹。此外，我们引入了T-SNE的时置变体，以专注于分子系统中的缓慢运动。这个时置的T-SNE有效地可视化了分子系统的缓慢动力学。
Molecular simulation trajectories represent high-dimensional data. Such data can be visualized by methods of dimensionality reduction. Non-linear dimensionality reduction methods are likely to be more efficient than linear ones due to the fact that motions of atoms are non-linear. Here we test a popular non-linear t-distributed stochastic neighbor embedding (t-SNE) method on analysis of trajectories of alanine dipeptide dynamics and Trp-cage folding and unfolding. Furthermore, we introduced a time-lagged variant of t-SNE in order to focus on slow motions in the molecular system. This time-lagged t-SNE efficiently visualizes slow dynamics of molecular systems.
