Pretorius, AJ, Khan, IA and Errington, RJ (2015) Cell lineage visualisation. Computer Graphics Forum, 34 (3). 21 - 30. ISSN 0167-7055
Abstract
Cell lineages describe the developmental history of cell populations and are produced by combining time-lapse imaging and image processing. Biomedical researchers study cell lineages to understand fundamental processes, such as cell differentiation and the pharmacodynamic action of anticancer agents. Yet, the interpretation of cell lineages is hindered by their complexity and insufficient capacity for visual analysis. We present a novel approach for interactive visualisation of cell lineages. Based on an understanding of cellular biology and live-cell imaging methodology, we identify three requirements: multimodality (cell lineages combine spatial, temporal, and other properties), symmetry (related to lineage branching structure), and synchrony (related to temporal alignment of cellular events). We address these by combining visual summaries of the spatiotemporal behaviour of an arbitrary number of lineages, including variation from average behaviour, with node-link representations that emphasise the presence or absence of symmetry and synchrony. We illustrate the merit of our approach by presenting a real-world case study where the cytotoxic action of the anticancer drug topotecan was determined.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2015 The Author(s). Computer Graphics Forum (c) 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. This is the peer reviewed version of the following article: [Pretorius, AJ, Khan, IA and Errington, RJ (2015) Cell lineage visualisation. Computer Graphics Forum, 34 (3). 21 - 30. ISSN 0167-7055, which has been published in final form at http://dx.doi.org/10.1111/cgf.12614. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |
Keywords: | visualisation; data visualisation; information visualisation; biological data; cell lineage; cell biology |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 May 2015 15:23 |
Last Modified: | 19 Dec 2022 13:31 |
Published Version: | http://dx.doi.org/10.1111/cgf.12614 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/cgf.12614 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:84341 |