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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 [23, 39]. Traditionally pictures in scientific publications were handRdrawn; however they are now almost exclusively computerRgenerated. 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 amount of scientific data increasing exponentially in all areas of biology, computational approaches for the analysis of data are now an essential part of modern research. 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. Visualisation is therefore central to enabling scientists to make sense of their data and communicate it to others in a concise and meaningful way. The interpretability of the output of text mining results (detecting bioprocesses, discovering hidden associations) can be improved by visualisation. However, biologists’ understanding of the range of visualisation techniques available, the most appropriate visual representation or encoding to use is currently limited to a small community.