Biological Visualisation Network

Biology is a visual science, from the way data is collected and analysed to how it is communicated to others. Traditionally pictures in scientific publications were hand-drawn; however they are now almost exclusively computer-generated. Biologists have been working with computer scientists and other experts in understanding graphical presentation techniques to automatically generate visualisations in biology. These range from graphical representations of molecules, representations of DNA sequences and genes, images of cells and organisms and metabolic pathways through to trees showing evolutionary processes.
Recently techniques have been developed that generate masses of data which can be used to analyse biological processes and functions, such as understanding how genes work and the effects they have on organisms. However this has presented a challenge in how to visually represent the data to allow biologists explore the data looking for patterns or trends that will help then understand the underlying biological processes. With the growing importance in visual techniques it is now the right time to spread the work about the benefits of biological visualisation.
To help more biologists discover and understand the new visualisation techniques and to engage other disciplines in helping to visually present this new data in a more effective manner we need to build a community resource for educating people. We will help introduce people with different expertise that can work together in coming up with new solutions and generally share their expertise and experience.
This proposal therefore plans to build a network of people interested in biological data visualisation. The network will develop a website to act as a resource for information on biological visualisation. We will also hold annual meetings for networking and educational purposes focussed around emerging trends in visualisation and challenges facing biology.

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.

The Network in Biological Visualisation will have a major impact on biologists across the UK in terms of their knowledge of available visualisation tools for exploring their data, making them more efficient and effective in making biological discoveries. The network will also clarify outstanding problems facing biologists exploring and analysing their data, making it possible for scientists in other disciplines collaborating with the biologists to develop appropriate tools for visual biological data analysis. The network will open up possibilities for project proposals for future interdisciplinary funding.