5 papers
Constructing Generalized Sample Transition Probabilities with Biased Simulations
Yanbin Wang, Jakub Rydzewski, Ming Chen
In molecular dynamics (MD) simulations, accessing transition probabilities between states is crucial for understanding kinetic information, such as reaction paths and rates. Howeve…
NeuralTSNE: A Python Package for the Dimensionality Reduction of Molecular Dynamics Data Using Neural Networks
Patryk Tajs, Mateusz Skarupski, Jakub Rydzewski
Unsupervised machine learning has recently gained much attention in the field of molecular dynamics (MD). Particularly, dimensionality reduction techniques have been regularly empl…
Illuminating Protein Dynamics: A Review of Computational Methods for Studying Photoactive Proteins
Sylwia Czach, Jakub Rydzewski, Wiesław Nowak
Photoactive proteins absorb light and undergo structural changes that enable them to perform essential biological functions. These proteins are critical for understanding light-ind…
maze: Heterogeneous Ligand Unbinding along Transient Protein Tunnels
Jakub Rydzewski
Recent developments in enhanced sampling methods showed that it is possible to reconstruct ligand unbinding pathways with spatial and temporal resolution inaccessible to experiment…
Rethinking Monocular Depth Estimation with Adversarial Training
Richard Chen, Faisal Mahmood, Alan Yuille +1
Monocular depth estimation is an extensively studied computer vision problem with a vast variety of applications. Deep learning-based methods have demonstrated promise for both sup…