01/03/2014 - 31/05/2017

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Biology is a visually grounded scientific discipline-from the way data is collected and analysed to the manner in which the results are communicated to others. Traditionally pictures in scientific publications were hand-drawn; however they are now almost exclusively computer-generated. Many areas in biology have historically evolved "standard" ways of representing biological information including phylogenetics, molecular structures, metabolic pathways and cell structures, however this has presented challenges in developing techniques for automatically generating these familiar representations. In more recent areas such as genomics, novel computer visualisation techniques have emerged for representing sequences, alignments and gene expression information.

With the exponentially increasing amount of scientific data available all areas of biology now rely heavily on computational approaches for the analysis of data. Although computational techniques facilitate the management and analysis of this data, it is critical that scientists be able to participate intimately in the analysis steps using qualitative and quantitative abstractions of the underlying data, therefore visualisation is central to enabling scientists to make sense of their data and communicate it to others in a concise and meaningful way. However, presently, biologists' understanding of the range of visualisation techniques available, the most appropriate visual representation or encoding to use is limited to a small community.

This proposal aims to bring together the expertise across the country and provide a focus for engaging with the wider community to educate biologists in new technologies, inspire computer scientists and related disciplines in the challenges associated with visualising biological data and to encourage ongoing collaboration in the field of data visualisation.
BioVisNet is a Research Councils project funded by BBSRC. Carried out in collaboration with and others. For further information please refer to
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Project Team

Alan Cannon
Research Fellow
+44 131 455 2437
Robert Kukla
Senior Research Fellow
+44 131 455 2738
Jessie Kennedy
Dean of Research and Innovation
+44 131 455 2772

Associated Publications