Student Posters Repository

Molecular dynamics (MD) simulations of proteins produce large data sets - long trajectories of atomic coordinates - and provide a representation of the sampling of a given molecule’s structural ensemble. A deep quantitative analysis using advanced machine learning techniques is a means to interpret MD trajectories. To visualize the conformational space of the molecule and properly identify conformational states, we suggest combining clustering methods and dimensionality reduction algorithms. We investigate different choices of features to represent individual structures, clustering algorithms, similarity metric, and methods to assign the number of clusters.