Visualizing DNA reaction trajectories with deep graph embedding
  approaches
Chenwei Zhang Khanh Dao Duc Anne Condon
Synthetic biologists and molecular programmers design novel nucleic acid
reactions, with many potential applications. Good visualization tools are
needed to help domain experts make sense of the complex outputs of folding
pathway simulations of such reactions. Here we present ViDa, a new approach for
visualizing DNA reaction folding trajectories over the energy landscape of
secondary structures. We integrate a deep graph embedding model with common
dimensionality reduction approaches, to map high-dimensional data onto 2D
Euclidean space. We assess ViDa on two well-studied and contrasting DNA
hybridization reactions. Our preliminary results suggest that ViDa's
visualization successfully separates trajectories with different folding
mechanisms, thereby providing useful insight to users, and is a big improvement
over the current state-of-the-art in DNA kinetics visualization.