TY - JOUR
T1 - RemBrain
T2 - Visualization and Data Analysis 2018, VDA 2018
AU - Ma, Chihua
AU - Pellolio, Filippo
AU - Llano, Daniel A.
AU - Stebbings, Kevin Ambrose
AU - Kenyon, Robert V.
AU - Marai, G. Elisabeta
N1 - Funding Information:
This work was supported in part by grants from the National Science Foundation NSF IIS-1541277 and NSF CNS-1625941 and from the National Institutes of Health, NIH NCI-R01CA225190 and NIH NCI-R01CA214825.
Publisher Copyright:
© 2018, Society for Imaging Science and Technology.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - We introduce a web-based visual comparison approach for the systematic exploration of dynamic activation networks across biological datasets. Understanding the dynamics of such networks in the context of demographic factors like age is a fundamental problem in computational systems biology and neuroscience. We design visual encodings for the dynamic and community characteristics of these temporal networks. Our multi-scale approach blends nested mosaic matrices that capture temporal characteristics of the data, spatial views of the network data, Kiviat diagrams and mirror glyphs that detail the temporal behavior and community assignment of specific nodes. A top design specifically targeted at pairwise visual comparison further supports the comparative analysis of multiple dataset activations. We demonstrate the effectiveness of this approach through a case study on mouse brain network data. Domain expert feedback indicates this approach can help identify trends and anomalies in the data.
AB - We introduce a web-based visual comparison approach for the systematic exploration of dynamic activation networks across biological datasets. Understanding the dynamics of such networks in the context of demographic factors like age is a fundamental problem in computational systems biology and neuroscience. We design visual encodings for the dynamic and community characteristics of these temporal networks. Our multi-scale approach blends nested mosaic matrices that capture temporal characteristics of the data, spatial views of the network data, Kiviat diagrams and mirror glyphs that detail the temporal behavior and community assignment of specific nodes. A top design specifically targeted at pairwise visual comparison further supports the comparative analysis of multiple dataset activations. We demonstrate the effectiveness of this approach through a case study on mouse brain network data. Domain expert feedback indicates this approach can help identify trends and anomalies in the data.
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U2 - 10.2352/J.ImagingSci.Technol.2017.61.6.060404
DO - 10.2352/J.ImagingSci.Technol.2017.61.6.060404
M3 - Conference article
C2 - 30505140
AN - SCOPUS:85056804326
SN - 2470-1173
JO - IS and T International Symposium on Electronic Imaging Science and Technology
JF - IS and T International Symposium on Electronic Imaging Science and Technology
Y2 - 28 January 2018 through 1 February 2018
ER -