Abstract
Background: Robust and useful tools for exploratory analysis in biosciences are still lagging behind the size and complexity of the biological datasets produced since the completion of the human genome in 2000. A possible reason is that developers are unlikely to understand domain and case-specific requirements of existing research questions. Methods: We formed a design team comprising a visualization expert, a Human Computer Interaction (HCI) researcher, bioinformatics domain experts, and the Principal Investigator (PI) as a `facilitator' filling the communication gap between them. We implemented co-design methodology. Results: We identified the need for an interactive visual analytic tool for exploratory analysis of biological data. We describe the process of developing MAHiCGO, a novel tool for the simultaneous visualization of MA Gene Expression data, Hi-C data and Gene Ontology (GO) information in an interactive manner for the exploratory analysis of biological data. Conclusion: The key finding of this research to include a facilitator role in the co-design is useful in the evolving fields of design research and of bioinformatics, merging computational sciences with biosciences. The findings support in understanding new functional roles in the field of design, in particular design of computer applications in highly complex domains such as bioinformatics, and for highly complex tasks such as exploratory tasks. The findings also stress on the key role of visualization to expand user cognitive capabilities, and of co-design for constant engagement of domain experts in the creation process.
Highlights
As an outcome of this co-design process, we developed a first prototype of the MAHiCGO visual analytic tool
REVIEW The following section starts with an overview of the historical development of the fields of bioinformatics and biovis with a specific focus on the three visualizations used in MAHiCGO: MA, Hi-C, and Gene Ontology (GO)
We could contribute to the design in short, well-organized and fruitful sessions.’’ And Mahi highlighting that ‘‘the Principal Investigator (PI) acted as the liaison between us and the Visualization/Human Computer Interaction (HCI) experts, and helped cascade all our feedback and comments to ensure we’re all aligned
Summary
Most users of this research generally view stages ‘B’ and ‘C’ as part of a single stage where innovative ways of visualization and representation of data can be very useful and can lead to potentially valuable discoveries through EDA (Fig. 1) [30], [31], [50] (Personal Communications, 2019-2020) In their 2019 comprehensive literature survey to compile ‘‘Tasks, Techniques, and Tools for Genomic Data Visualization’’, Nusrat et al [24] highlight how complex information from different sources need to be integrated into visualization in order to understand and interpret genomic information and the corresponding complex biological systems.
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