Difference between revisions of "BanghamLabSVN"

From BanghamLab
Jump to navigation Jump to search
 
(16 intermediate revisions by the same user not shown)
Line 1: Line 1:
 
 
__NOTOC__
 
__NOTOC__
 
[[Software| Return to Software]]<br><br>
 
[[Software| Return to Software]]<br><br>
=DArT_Toolbox File level help=
+
=<span style="color: darkred">DArT_Toolshed</span>=
==[[Toolboxes file level help|<span style="color: Navy">Toolboxes</span>]] ==
+
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 0.36 GB 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>
==[[Algorithms file level help|<span style="color: Navy">Algorithms </span>]] ==
+
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. MTtbox is similar, biological models are succinctly coded into interaction functions. The physics and numerics are accessible but elsewhere. Stick in a breakpoint and step through algorithms to see how they work.<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. We use Windows, Mac OS and Linux.
 +
<br><br>
 +
In keeping with Matlab conventions, most of our functions have help comments in the first few lines of the file. This means that Matlab itself indexes this file-level help automatically. To allow you to see the scope of our work, this help has been listed on the following pages.
 +
==[[Toolboxes file level help|<span style="color: Navy">Toolboxes: File level help</span>]] ==
 +
Total 2828 functions.
 +
==[[Algorithms file level help|<span style="color: Navy">Algorithms: File level help </span>]] ==
 
Total 252 functions.
 
Total 252 functions.
==[[Attachments file level help|<span style="color: Navy">Attachments </span>]] ==
+
==[[Attachments file level help|<span style="color: Navy">Attachments: File level help </span>]] ==
==[[IOMethods  file level help|<span style="color: Navy">IOMethods  </span>]] ==
+
Total 107 functions.
==[[ToolBag file level help|<span style="color: Navy">ToolBag </span>]] ==
+
==[[IOMethods  file level help|<span style="color: Navy">IOMethods: File level help </span>]] ==
 +
Total 4 functions.
 +
==[[ToolBag file level help|<span style="color: Navy">ToolBag: File level help </span>]] ==
 +
Total 185 functions.

Latest revision as of 10:49, 23 May 2013

Return to Software

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 0.36 GB 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. MTtbox is similar, biological models are succinctly coded into interaction functions. The physics and numerics are accessible but elsewhere. Stick in a breakpoint and step through algorithms to see how they work.

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. We use Windows, Mac OS and Linux.

In keeping with Matlab conventions, most of our functions have help comments in the first few lines of the file. This means that Matlab itself indexes this file-level help automatically. To allow you to see the scope of our work, this help has been listed on the following pages.

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.