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Cerebral : visualizing multiple experimental conditions on a graph with biological context Barsky, Aaron
Abstract
Systems biologists use interaction graphs to model the behaviour of biological systems at the molecular level. In an iterative process, such biologists observe the reactions of living cells under various experimental conditions, view the results in the context of the interaction graph, and then propose changes to the graph model. These graphs represent dynamic knowledge of the biological system being studied and evolve as new insight is gained from the experimental data. While numerous graph layout and drawing packages are available, these tools did not fully meet the needs of our immunologist collaborators. In this thesis, we describe the data display needs of these immunologists and translate these needs into visual encoding decisions. These decisions led us to create Cerebral, a system that uses a biologically guided graph layout and incorporates experimental data directly into the graph display. Our graph layout algorithm uses simulated annealing with constraints, optimized with a uniform grid to have an expected runtime of o(E/V). Small multiple views of different experimental conditions and a measurement-driven parallel coordinates view enable correlations between experimental conditions to be analyzed at the same time that the measurements are viewed in the graph context. This combination of coordinated views allows the biologist to view the data from many different perspectives simultaneously. To illustrate the typical analysis tasks performed, we analyze two datasets using Cerebral. Based on feedback from our collaborators, we conclude that Cerebral is a valuable tool for analyzing experimental data in the context of an interaction graph model.
Item Metadata
| Title |
Cerebral : visualizing multiple experimental conditions on a graph with biological context
|
| Creator | |
| Publisher |
University of British Columbia
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| Date Issued |
2008
|
| Description |
Systems biologists use interaction graphs to model the behaviour of biological systems at the molecular level. In an iterative process, such biologists
observe the reactions of living cells under various experimental conditions,
view the results in the context of the interaction graph, and then propose
changes to the graph model. These graphs represent dynamic knowledge of
the biological system being studied and evolve as new insight is gained from
the experimental data. While numerous graph layout and drawing packages
are available, these tools did not fully meet the needs of our immunologist
collaborators. In this thesis, we describe the data display needs of these
immunologists and translate these needs into visual encoding decisions.
These decisions led us to create Cerebral, a system that uses a biologically guided graph layout and incorporates experimental data directly into
the graph display. Our graph layout algorithm uses simulated annealing with
constraints, optimized with a uniform grid to have an expected runtime of
o(E/V). Small multiple views of different experimental conditions and a
measurement-driven parallel coordinates view enable correlations between
experimental conditions to be analyzed at the same time that the measurements are viewed in the graph context. This combination of coordinated
views allows the biologist to view the data from many different perspectives
simultaneously. To illustrate the typical analysis tasks performed, we analyze two datasets using Cerebral. Based on feedback from our collaborators,
we conclude that Cerebral is a valuable tool for analyzing experimental data
in the context of an interaction graph model.
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| Extent |
2737426 bytes
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| Genre | |
| Type | |
| File Format |
application/pdf
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| Language |
eng
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| Date Available |
2008-12-08
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0051296
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2008-11
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International