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Lookup NU author(s): Dr Sara Johansson Fernstad, Dr Alexander MacquistenORCiD, Professor Janet Berrington, Professor Nicholas EmbletonORCiD, Professor Christopher StewartORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Studies of genome sequenced data are increasingly common in many domains. Technological advances enable detection of hundreds of thousands of biological entities in samples, resulting in extremely high dimensional data. To enable exploration and understanding of such data, efficient visual analysis approaches are needed that take domain and data specific requirements into account. Based on a survey with bioscience experts, this paper suggests a categorisation and a set of quality metrics to identify patterns of interest, which can be used as guidance in visual analysis, as demonstrated in the paper.
Author(s): Johansson Fernstad S, Macquisten A, Berrington J, Embleton N, Stewart C
Editor(s): Turkay, Cagatay and Vrotsou, Katerina
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: EuroVis Workshop on Visual Analytics (EuroVA)
Year of Conference: 2020
Acceptance date: 13/04/2020
Date deposited: 21/06/2020
Publisher: The Eurographics Association
URL: https://doi.org/10.2312/eurova.20201083
DOI: 10.2312/eurova.20201083
Library holdings: Search Newcastle University Library for this item
ISBN: 9783038681168