Visualizing DNA reaction trajectories with deep graph embedding approaches
This provides a visualization tool for synthetic biologists and molecular programmers to better understand DNA reaction simulations, though it appears incremental as it builds on existing dimensionality reduction techniques.
The paper tackles the problem of visualizing complex DNA reaction folding trajectories by introducing ViDa, a deep graph embedding approach that maps high-dimensional data to 2D space, with preliminary results showing it successfully separates trajectories with different folding mechanisms and improves over current state-of-the-art methods.
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.