Collaborations and training in integrative biology

The prevalence of first systems and then synthetic biology in BBSRC and wider UK research funding calls, the establishment of The Genome Analysis Centre (TGAC), the fact that the term ‘big data’ is mentioned in nearly every meeting of any type about the biological sciences … all these point to the irreversible integration of mathematics into biology.

This blog post is for two groups of people: plant scientists who feel they lack the expertise to confidently maneuver in the world of integrative biology; and theoreticians either interested in plant science, or who would rather not have to spend quite as much time dealing with the mathematical problems of the plant scientists in their professional or non-professional circles. (more…)

CellSet confocal image analysis

Categories: guest blogger, resource
Comments: No Comments
Published on: April 25, 2013

Michael Pound is an image analyst at CPIB. He kindly agreed to write a guest post for GARNet on his recent project, confocal image analysis software CellSeT

CellSeT, which was recently published in Plant Cell (24:1353), is open source software which analyses confocal images of plant cells. CellSeT can extract information including fluorescence and membrane polarity objectively and quickly. A simple workflow begins with the program filtering noise out of the image, and then it segments the image into individual cells. Confocal images can produce excellent slices through root meristems, however some incorrect segmentation is inevitable deeper into the root tissue. CellSeT was designed with this in mind, and the user can then manually refine the cell segments. This optional manual step is followed by an automatic refinement using active contours, aimed at improving accuracy and reducing subjectivity. Finally the cells can be manually assigned semantic tags and measured. Plugins, which are also open source, allow users to carry out more specialised functions, or cell geometries can be exported into modelling packages such as OpenAlea.

CellSeT will be useful to researchers who produce confocal images at a cell scale, usually of root tissue, although CellSeT has been shown to work on other regions such as the plant leaf. The plugin architecture allows anyone with a basic programming knowledge to perform additional image analysis within each cell. For example, an existing plugin is used to detect and quantify nuclear fluorescence in a separate colour channel to the cell walls.

You can download CellSeT from Sourceforge. Due to its use of Windows graphics libraries, CellSeT only runs in Windows. If you don’t use Windows, you will have to run a virtual windows environment to use it. CellSeT works successfully on software such as parallels if this is necessary.

Image credits: CPIB 

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