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Visual Analytics of Signalling Pathways Using Time Profiles

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Signal and Image Analysis for Biomedical and Life Sciences

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 823))

Abstract

Data visualisation is usually a crucial first step in analysing and exploring large-scale complex data. The visualisation of proteomics time-course data on post-translational modifications presents a particular challenge that is largely unmet by existing tools and methods. To this end, we present Minardo, a novel visualisation strategy tailored for such proteomics data, in which data layout is driven by both cellular topology and temporal order. In this work, we utilised the Minardo strategy to visualise a dataset showing phosphorylation events in response to insulin. We evaluated the visualisation together with experts in diabetes and obesity, which led to new insights into the insulin response pathway. Based on this success, we outline how this layout strategy could be automated into a web-based tool for visualising a broad range of proteomics time-course data. We also discuss how the approach could be extended to include protein 3D structure information, as well as higher dimensional data, such as a range of experimental conditions. We also discuss our entry of Minardo in the international DREAM8 competition.

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Notes

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    This famous graphic shows Napoleon’s disastrous Russian campaign of 1812 – the graphic is regarded as an exemplar by many data visualisation specialists [4].

  2. 2.

    http://www.jameslab.com.au

  3. 3.

    http://locate.imb.uq.edu.au/

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Acknowledgements

We gratefully acknowledge helpful conversations with our colleagues Prof. David James, Dr Sean Humphrey, Dr Adelle Coster, Annabel Minard, and Beverley Murrow.

Author information

Authors and Affiliations

  1. Garvan Institute of Medical Research, Sydney, NSW, Australia

    David K. G. Ma, Sandeep Kaur & Seán I. O’Donoghue

  2. The University of NSW, Sydney, NSW, Australia

    David K. G. Ma, Sandeep Kaur & Michael Bain

  3. Digital Productivity Flagship, CSIRO, Sydney, NSW, Australia

    Christian Stolte & Seán I. O’Donoghue

Authors
  1. David K. G. Ma
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  2. Christian Stolte
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  3. Sandeep Kaur
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  4. Michael Bain
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  5. Seán I. O’Donoghue
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Corresponding author

Correspondence to Seán I. O’Donoghue .

Editor information

Editors and Affiliations

  1. Digital Productivity Flagship, CSIRO, Sydney, New South Wales, Australia

    Changming Sun

  2. Digital Productivity Flagship, CSIRO, Sydney, New South Wales, Australia

    Tomasz Bednarz

  3. The University of Aizu, Fukushima, Japan

    Tuan D. Pham

  4. Digital Productivity Flagship, CSIRO, Sydney, New South Wales, Australia

    Pascal Vallotton

  5. Digital Productivity Flagship, CSIRO, Sydney, New South Wales, Australia

    Dadong Wang

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Ma, D.K.G., Stolte, C., Kaur, S., Bain, M., O’Donoghue, S.I. (2015). Visual Analytics of Signalling Pathways Using Time Profiles. In: Sun, C., Bednarz, T., Pham, T., Vallotton, P., Wang, D. (eds) Signal and Image Analysis for Biomedical and Life Sciences. Advances in Experimental Medicine and Biology, vol 823. Springer, Cham. https://doi.org/10.1007/978-3-319-10984-8_1

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