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Current activity: a collaboration with the CoenLab with the aim of understanding how patterns of gene activity in biological organs influence the developing shape. The BanghamLab is focussed on the conceptual underpinning: concepts captured in computational growth models, experimental data visualisation and analysis.

Computational biology toolboxes

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Growing complex biological shapes from patterns of gene expression

The growth of a complex snapdragon flower shape. Key to the model, is an hypothesis on how organisers control the axes along which growth occurs. The organisers are shown in cyan and green. On the right are the shapes of two symmetrical mutants computed from the same model (hypotheses).

The Growing Polarised Tissue Framework for understanding and modelling the relationship between gene activity and the growth of shapes such leaves, flowers and animal embryos (Kennaway et al 2011). The GPT-framework was used to capture an understanding of (to model) the growing leaf (Kuchen et al 2012) and Snapdragon flower Green et al 2011. The Snapdragon model was validated by comparing the results with other mutant and transgenic flowers Cui et al 2010.

More details on growth

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VolViewer

<imgicon>VolViewer-logo.png|120px|VolViewer</imgicon>

For viewing and measuring biological images. What? How? Where? Tutorials: from the beginning Download (Windows, Mac, Linux) Output from VolViewer has appeared in: Front cover: Handbook of Plant Science | Front cover: The Plant Cell | Royal Microscopical Society: Infocus Magazine | Bundled with the Bioptonic 3001 scanner: Bioptonics Viewer | The Guardian newspaper: 3D Fruit fly | Qt Ambassador program | Triffid Nurseries website

VolViewer uses OpenGL and Qt to provide a user friendly application to interactively explore and quantify multi-dimensional biological images. It has been successfully used in our lab to explore and quantify confocal microscopy and optical projection tomography images. It is open-source and is also compatible with the Open Microscopy Environment (OME).

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AAMToolbox

<imgicon>AAMToolbox_logo.jpg|120px|AAMToolbox</imgicon>

For analysing populations of shapes and colours within the shapes using principal component analysis. What? How? Where? Tutorials: from the beginning Download (PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed Matlab 30 day free trial and student edition)

The AAMToolbox enables the user analyse the shape and colour of collections of similar objects. Originally developed to analyse face shapes for lipreading, we have used it extensively for analysing the shapes of leaves and petals. The analysis can be applied to art, for example, finding systematic differences between portraits by, for example, Rembrandt and Modigliani.