The effective visualization and presentation of biological data is of critical importance to research scientists. The increasing rate at which experiments generate data has only exacerbated the problem. While bioinformatics datasets continue to increase in size and complexity, the shift to adopt new user interface (UI) paradigms has historically lagged. Consequently, a major bottleneck for analysis of next-generation sequencing data is the continued use of UIs primarily inspired from the 1990’s through the early 2000’s. This paper presents the novel use of virtual reality (VR) as a medium for visualizing genomic, transcriptomic and proteomic data. Using the Gria2 (GluR2 or GluA2) gene and its associated gene products as our main objects of interest, we present Gria2-Viewer, a proof of concept software tool for visualizing any gene variant within the Gria2 locus. For any given genomic or transcriptomic variant of Gria2, we can quickly visualize its position on the protein subunit, rendered as a secondary structure. We also present a design for an experimental case study which compares our software versus a “traditional” workstation for ascertaining the severity of any Gria2 variant and its location within a 3d representation of the protein.
Department, Program, or Center
Thomas H. Gosnell School of Life Sciences (COS)
Gary R. Skuse
Zhang, Jimmy Fan, "Exploring GRIA2 Sequence Variations Using Virtual Reality" (2017). Thesis. Rochester Institute of Technology. Accessed from
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