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=DArT_Toolshed= | =DArT_Toolshed= | ||
The DArT_Toolshed is a repository of software developed on BBSRC grant BB/F005555/1 ''A Multiscale Approach to Genes Growth and Geometry'' (a collaboration with the [http://rico-coen.jic.ac.uk/index.php/Main_Page CoenLab]). A 0.6 MB zipped copy (21st May 2013) is available [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/DArT_Toolbox_Download.zip <span style="color: Gray">'''''DArT_Toolbox_Download.zip''''' Revision 4699</span>]<br><br> | The DArT_Toolshed is a repository of software developed on BBSRC grant BB/F005555/1 ''A Multiscale Approach to Genes Growth and Geometry'' (a collaboration with the [http://rico-coen.jic.ac.uk/index.php/Main_Page CoenLab]). A 0.6 MB zipped copy (21st May 2013) is available [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/DArT_Toolbox_Download.zip <span style="color: Gray">'''''DArT_Toolbox_Download.zip''''' Revision 4699</span>]<br><br> | ||
Most of the software is written in Matlab. Exceptions include VolViewer which uses OpenGL extensively. <br><br> | |||
'''Why Matlab?''' The language suits our problems. For example, ''GFtbox'' - the reasoning goes like this. Tissue is represented by a thin 3D mesh. Growth factors levels vary spatially forming patterns, e.g. Fig. 1. Here there are two, ''A'' and ''B''. We might make the hypothesis that the growth rate is specified by ''A'' but partially inhibited by ''B'' (inhibited by an amount ''K''). This is a simple idea that can be expressed in Matlab equally simply by writing ''Growth=A .* inh(K, B)''. This is because variables ''A'' and ''B'' can represent vectors - in this case a level for each node in the mesh. We also define a general inhibition function (''inh''). It means that it is straightforward to convert our thoughts on the biology into a programmatic description of a computational model. <br><br> | |||
Moreover, the language is well documented with lots of convenient tools. In particular, Matlab has an extensive library of portable graphical user interface (GUI) functions - and this is convenient for producing tools to visualise the mesh and patterns of growth factors. | |||
==[[Toolboxes file level help|<span style="color: Navy">Toolboxes: File level help</span>]] == | ==[[Toolboxes file level help|<span style="color: Navy">Toolboxes: File level help</span>]] == | ||
Total 2828 functions. | Total 2828 functions. | ||
Revision as of 20:13, 21 May 2013
DArT_Toolshed
The DArT_Toolshed is a repository of software developed on BBSRC grant BB/F005555/1 A Multiscale Approach to Genes Growth and Geometry (a collaboration with the CoenLab). A 0.6 MB zipped copy (21st May 2013) is available DArT_Toolbox_Download.zip Revision 4699
Most of the software is written in Matlab. Exceptions include VolViewer which uses OpenGL extensively.
Why Matlab? The language suits our problems. For example, GFtbox - the reasoning goes like this. Tissue is represented by a thin 3D mesh. Growth factors levels vary spatially forming patterns, e.g. Fig. 1. Here there are two, A and B. We might make the hypothesis that the growth rate is specified by A but partially inhibited by B (inhibited by an amount K). This is a simple idea that can be expressed in Matlab equally simply by writing Growth=A .* inh(K, B). This is because variables A and B can represent vectors - in this case a level for each node in the mesh. We also define a general inhibition function (inh). It means that it is straightforward to convert our thoughts on the biology into a programmatic description of a computational model.
Moreover, the language is well documented with lots of convenient tools. In particular, Matlab has an extensive library of portable graphical user interface (GUI) functions - and this is convenient for producing tools to visualise the mesh and patterns of growth factors.
Toolboxes: File level help
Total 2828 functions.
Algorithms: File level help
Total 252 functions.
Attachments: File level help
Total 107 functions.
IOMethods: File level help
Total 4 functions.
ToolBag: File level help
Total 185 functions.