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Synopset: multiscale visual abstraction set for explanatory analysis of dna nanotechnology simulations

Deng Luo1
PTL NANO
VOLUME 01, ISSUE02
DOI- REGISTERING
Acknolowdgement NA

Keyword Highlighted

Application-Motivated Visualization, Data Abstractions & Types, Communication/Presentation, Storytelling, Temporal Data

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Abstract
We propose a new abstraction set (SynopSet) that has a continuum of visual representations for the explanatory analysis of molecular dynamics simulations (MDS) in the DNA nanotechnology domain. By re-purposing the commonly used progress bar and designing novel visuals, as well as transforming the data from the domain format to a format that better fits the newly designed visuals, we compose this new set of representations. This set is also designed to be capable of showing all spatial and temporal details, and all structural complexity, or abstracting these to various degrees, enabling both the slow playback of the simulation for detailed examinations or very fast playback for an overview that helps to efficiently identify events of interest, as well as several intermediate levels between these two extremes. For any pair of successive representations, we demonstrate smooth, continuous transitions, enabling users to keep track of relevant information from one representation to the next. By providing multiple representations suited to different temporal resolutions and connected by smooth transitions, we enable time-efficient simulation analysis, giving users the opportunity to examine and present important phases in great detail, or leverage abstract representations to go over uneventful phases much faster. Domain experts can thus gain actionable insight about their simulations and communicate it in a much shorter time. Further, the novel representations are more intuitive and also enable researchers unfamiliar with MDS analysis graphs to better understand the simulation results. We assessed the effectiveness of SynopSet on 12 DNA nanostructure simulations together with a domain expert. We have also shown that our set of representations can be systematically located in a visualization space, dubbed SynopSpace, composed of three axes: granularity, visual idiom, and information layout type. Proposed at the end are general guidelines on the use of SynopSpace to generate a new SynopSet for the visualization of other dynamic processes involving hierarchical structures.

Introduction
DNA nanotechnology [1] uses DNA in its double helix form as building blocks for more complex structures, by leveraging the Watson-Crick base pairing rule, rather than as a genetic information carrier. Two main methods have been developed to assemble DNA nanostructures: scaffolded DNA origami [2] and DNA bricks [3–5]. The assembled structures are ever-increasing and range from simple geometric primitives to large multi-component systems with dynamic behavior. Well-designed nanostructures have shown promising application scenarios, ranging from fundamental studies by acting as substrates for biochemical analysis [6], to medical applications by facilitating targeted drug delivery [7]. A typical current workflow in this domain is to first design the shape of the nanostructure with computer aided design tools. These will usually be able to generate specific DNA sequences for all the strands in the designed structure. Then the structure will be subject to molecular dynamics simulation to investigate its structural stability and dynamic behavior; if it is not stable, or lacks desired properties, several rounds of modifications followed by simulation loops will be performed until the designer is satisfied. Then the finalized DNA sequences will be ordered as oligonucleotides from commercial companies and lab experiments will be performed to assemble the designed structure. Finally, tests will be run, such as observing the shape of the final assembled structure under the microscope. DNA simulations may include tens of thousands of atoms, and many thousands of time steps. If a domain expert wishes to analyze a simulation in atomistic detail through visualization, they will therefore be presented with a great deal of information per step. Visualizing all time steps in a continuous playback presents a vastly greater challenge still, for the sheer number of time steps means that in total, there are thousands of positions to analyze over millions of simulation steps, resulting in an enormous amount of data. Fast playback can in principle keep the analysis reasonably short, but in practice, this means a very large amount of information per second will be presented to the expert, vastly exceeding their ability to comprehend it and make use of it. Playing the simulation at a sufficiently low speed to understand it entails many hours of playback, sometimes more. Yet MDS often exhibit long periods devoid of any important events, which would make such a visualization process not only long and tedious, but very inefficient. Such simulations are sometimes visualized at a slightly coarser granularity, by representing only nucleotides and not individual atoms, which somewhat reduces the amount of information per frame, but falls far short of fully solving the problem. A suitable solution to this problem would provide experts with abstract visualizations to efficiently analyze uneventful phases of their simulations, while still getting an overview of the simulation’s state and its dynamics; but it also needs to provide them with very detailed visualizations for critical phases of the simulation. It would also need to provide smooth, continuous transitions between these representations, for a seamless and time-efficient experience. To solve this, we take advantage of the hierarchical nature of DNA structures to propose involves seven different representations, ranging from very abstract to very detailed. The more abstract ones present less information per simulation step, and involve less (or no) motion of the visual elements themselves, aside from their colors. This makes such representations comfortable to view at high playback speeds, and thus suited to the relatively uneventful phases of DNA simulations. They provide an overview of what happens over a long period of simulation time, but in a short amount of visualization time. On the other hand, they present insufficient detail for the analysis of important events, where experts need detailed information to gain insight into their DNA systems. For such cases, more detailed representations are required, which in turn require lower playback speeds. In summary, the contributions of our solution are: • A new abstraction set (SynopSet) that has a continuum of visual representations for the explanatory analysis of MDS for DNA nanotechnology. • For each representation, i.e., each SynoPoint in SynopSet, we lay out the design rationale and the use of the Ballchain technique used in 5 different SynoPoints. We also demonstrate smooth and continuous transitions between consecutive SynoPoints. • We show the effectiveness of this novel approach to visual organization and information abstraction on the analysis of seven DNA nanotechnology simulations, generate a summary video, and report the feedback from an expert in DNA nanotechnology. • Finally, we observe that all SynoPoints in SynopSet can be located in a visualization space dubbed SynopSpace, composed of three axes: granularity, visual idiom, and information layout type. We also propose general guidelines on how SynopSpace can be used to generate a new SynopSet for the visualization of other dynamic processes involving hierarchical structures.