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Theses

Spatially Integrated Abstraction of Genetic Molecules

Sarkis Halladjian 1, 2, 3
3 AVIZ - Analysis and Visualization
Inria Saclay - Ile de France, LRI - Laboratoire de Recherche en Informatique
Abstract : The human genome consists mainly of DNA, a macromolecule consisting of a long linear sequence of bases, tightly packed to fit in the relatively small nucleus. The packing gives rise to multiple hierarchical organizational levels. Recent research has shown that, along with the linear sequence, the spatial arrangement of the genome plays an important role in the genome’s function and activity. The visualization of both linear and spatial aspects of genome data is therefore necessary. In this thesis, we focus on the concept of continuous visual abstraction for multiscale data, applied to the visualization of the human genome. Visual abstraction is a concept inspired by illustrations that makes the job of visual processing simpler, by guiding the attention of the viewer to important aspects. We first extract characteristics of multiscale data and makes a parallel comparison between genome and astronomical data. The existing differences create the need for different approaches. A common point however is the need for continuous transitions that helps viewers grasp the relationships and relative size differences between scales. To satisfy the conditions posed by the two aspects of the multiscale genome data, we present two conceptual frameworks, based on the same data. The first framework, ScaleTrotter, represents the spatial structure of the genome, on all available levels. It gives users the freedom to travel from the nucleus of a cell to the atoms of the bases, passing through the different organizational levels of the genome. To make the exploration of the structure of all levels possible, smooth temporal transitions are used. Even though all the scales are not simultaneously visible, the temporal transition used superimposes two representations of the same element at consecutive scales emphasizing their relationship. To ensure the understandability and interactivity of the data, unnecessary parts of the data are abstracted away with the use of a scale-dependent camera. The second framework, Multiscale Unfolding, focuses on aspects that are not visible in ScaleTrotter: the linear sequence and a simultaneous overview of all the organizational levels. The data is straightened to unfold the packing that occurs on several levels in a way that conserves the connectivity between the elements. To represent all the available levels, we use smooth spatial transitions between the levels. These spatial transitions are based on the same concept of the temporal transitions of the previous framework, superimposing scales and emphasizing on their relationship and size difference. We introduce an interaction technique called Multiscale Zliding that allows the exploration of the data and further emphasizes the size differences between the levels. In each framework, one of either linear of spatial aspect of genome data is sacrificed to emphasize the other. The thesis concludes with a discussion about the possibility of combining the two frameworks, minimizing the sacrifices to explore the two equally important aspects of the genome. In this thesis, we take a step closer to fully understanding the activity of the genome.
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Sarkis Halladjian. Spatially Integrated Abstraction of Genetic Molecules. Human-Computer Interaction [cs.HC]. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASG056⟩. ⟨tel-03177653⟩

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