Paper
8 March 2011 Visualizing large, high-throughput datasets based on the cognitive representation of biological pathways
Axel Nagel, Marc Lohse, Anthony Bolger, Mark Stitt, Björn Usadel
Author Affiliations +
Proceedings Volume 7865, Human Vision and Electronic Imaging XVI; 78650H (2011) https://doi.org/10.1117/12.881998
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
The data explosion in the biological sciences has led to many novel challenges for the individual researcher. One of these is to interpret the sheer mass of data at hand. Typical high-throughput data sets from transcriptomic data can easily comprise hundred thousand data points. It is thus necessary to provide tools to interactively visualize these data sets in a way that aids in their interpretation. Thus we have developed the MAPMAN application. This application renders individual data points from different domains as different glyphs that are color coded to reflect underlying changes in the magnitude/abundance of the underlying data. In order to augment the human comprehensibility of the biologist domain experts these data are organized on meaningful pathway diagrams that the biologist has encountered numerous times. Using these representations together with a high level organization thus helps to quickly realize the main outcome of such a high throughput study and to further decide on additional tasks that should be performed to explore the data.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Axel Nagel, Marc Lohse, Anthony Bolger, Mark Stitt, and Björn Usadel "Visualizing large, high-throughput datasets based on the cognitive representation of biological pathways", Proc. SPIE 7865, Human Vision and Electronic Imaging XVI, 78650H (8 March 2011); https://doi.org/10.1117/12.881998
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KEYWORDS
Visualization

Mode conditioning cables

Proteins

Digital filtering

Data corrections

Data modeling

Electronic imaging

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