RemBrain: Exploring dynamic biospatial networks with mosaicmatrices and mirror glyphs

Chihua Ma, Filippo Pellolio, Daniel A. Llano, Kevin Ambrose Stebbings, Robert V. Kenyon, G. Elisabeta Marai

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
JournalIS and T International Symposium on Electronic Imaging Science and Technology
StatePublished - Nov 1 2017
EventVisualization and Data Analysis 2018, VDA 2018 - Burlingame, United States
Duration: Jan 28 2018Feb 1 2018

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Chemistry(all)
  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications


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