GFtbox Tutorial pages

GFtbox Details

Three ways to use GFtbox

1) Doing everything from the Graphical User Interface (GUI). See here for the best way to start working with GFtbox

2) Do only some things from the GUI. See here for the best way to develop ideas on the growth of shape. Use the GUI to generate the mesh (canvas) and create growth factors (morphogens - in other words declare the variables) but capturing your ideas on how the regulatory processes work in, what we call, the interaction function.

For an introduction to the output and results, see here.

3) Without the GUI. Running models without the GUI, see here. For example, run many examples (instances) of a pre-existing project on a cluster. This is the best way to explore the parameter space of a model for comparison with biological observations. We use this extensively once we have roughed out the basic ideas interactively.

1 Modelling using the Graphical User Interface

Isotropic growth

1 A

For tutorial on uniform growth click here. Consider a disc shaped canvas (tissue) in which the specified growth is uniform, isotropic and on both sides. Into what shape will the disc grow? This model is as simple as it gets. Notice that, during growth, the mesh is automatically subdivided. Notice also that the final surface is not quite flat. This is because, to allow it to deform in 3D, it is not flat initially. There are options to initialise a flat mesh and others to force it to remain flat - see options on the GUI (hover over controls to get prompts). In the absence of a polariser (there is no polariser in this example) growth will be isotropic, in other words growth in the plane of the canvas will be the average of what is specified for Kapar and Kaper (A side) and Kbpar and Kbper (B side).

<wikiflv width="300" height="300" logo="false" loop="true" background="white">GPT_tut_uniform_20110527-0003.flv|GPT_tut_uniform_20110527-0003_Last.png</wikiflv>

1 B

For tutorial on non-uniform growth click here Consider a disc shaped canvas (tissue) in which the non-uniform specified growth increases in proportion to the distance from the centre. Into what shape will the disc grow? Already we are into the realms of modelling biological systems. Compare this result with the discussion of Lily petals and Gaussian curvature (Lianga and Mahadevana,Sharon, Marder and Swinney,Nath, Crawford, Carpenter and Coen ).

<wikiflv width="300" height="300" logo="false" loop="true" background="white">GPT_tut_uniform_20110527-0006.flv|GPT_tut_uniform_20110527-0006_First.png</wikiflv> Note: this model should have many more finite elements

Adding polariser

1 C

For tutorial on uniform growth non-uniform polariser click here In the presence of polariser, GFtbox growth will be anisotropic, in other words growth in the plane of the canvas can be different parallel and perpendicular to the axis of the polariser: Kapar and Kaper (A side) and Kbpar and Kbper (B side). We now add polariser. Start with example A - uniform growth - and add a radial polarising gradient. Arrows show the direction of the gradient. They are turned on using the Panel:Plot option:Pol. grad. tick box. The gradient defines local directions and local growth can be specifed either parallel to (Kpar) or perpendicular to (Kper) that direction. Given a uniform pattern of specified growth parallel to the polariser and zero specified growth perpendicular to the polariser. What will be the final shape?

<wikiflv width="300" height="300" logo="false" loop="true" background="white">GPT_in_the_beginning_2_20110510-0003.flv|GPT_in_the_beginning_2_20110510-0003_First.png</wikiflv>Note: the gradient of the polariser, green to cyan, is shown using the arrows. Specified growth rate parallel to the arrows, red, is uniform.

2 Modelling using a combination of GUI and interaction function

Interaction functions - programmatic modelling.

The full specification of a GFtbox model is stored in a combination of the mesh data structure (Mesh) and the interaction function. The Mesh stores all the physical properties of the system: spatial structure, mechanical properties, etc. It is usually set up using the GUI. The Mesh is stored on disc as a Matlab data file (.mat) and in memory as a data structure (m). The interaction function (a Matlab program file .m) contains all the details of the growth regulation system: morphogen concentrations, signal interactions etc.

When a new project is first edited the interaction function is generated automatically. Thereafter, it is automatically kept in synchrony with the GUI. It is divided into several sections. Some are generated automatically and should not be edited. Others are set aside for the user to specify the model. To ensure that the automatic and manual edits are synchronised always invoke the Editor from the GUI (Panel: Interaction Function: Edit).

2 A

Basic interaction function The Mesh was setup using the GUI and code articulating the regulatory model was edited into the 'interaction function. This described in the next tutorial. The code was:

   if (Steps(m)==0) && m.globalDynamicProps.doinit  % Initialisation code.
       id_a_p(m.nodes(:,1)<-0.03)=1; % setup region for A where identity factor A is represented by id_a_p
       id_b_p(m.nodes(:,2)<-0.01)=1; % setup region for B
   else
       % @@KRN Growth Regulatory Network
       kapar_p(:) = id_a_l .* inh(1,id_b_l); % growth rate
       kaper_p(:) = kapar_p; % isotropic growth
       kbpar_p(:) = kapar_p; % same on both sides of the sheet
       kbper_p(:) = kapar_p; % same
       knor_p(:)  = 0;       % thickness not growing
   end

For tutorial on a basic interaction function click here The tutorial explains how the code shown above appears in the interaction function. To create the interaction function, first create and save a project (see above) then click Panel:Interaction function:Edit. The interaction function will contain all the default variables and any patterns of variables (Kapar, etc.) that have already been set through the GUI. Types of morphogens and factors are given here.

<wikiflv width="300" height="300" logo="false" loop="true">GPT_why_matlab-2011-05-05-0005.flv|GPT_why_matlab-2011-05-05-0005_First.png‎</wikiflv>

Details

Play and the mesh will grow and subdivide. Normally we do not want to see the mesh. Red is growth rate

2 B

Interaction function in detail (A newly created, empty, interaction function is shown here.)

Tutorial on the interaction function details click here Types of morphogens and factors are given here.	<wikiflv width="300" height="300" logo="false" loop="true">GPT_why_matlab-2011-05-05-0005.flv|GPT_why_matlab-2011-05-05-0005_First.png‎</wikiflv> Play submodel 1
Submodel 2	<wikiflv width="300" height="300" logo="false" loop="true">GPT_why_matlab-2011-05-05-0005.flv|GPT_why_matlab-2011-05-05-0005_First.png‎</wikiflv> Play submodel 2

Output and Results

2 C Illustrating two independent ways to form shapes and the use of submodels.

Conclusion: interesting shapes can be generated either by patterns of differential growth or patterns of local growth axes.

Tutorial on two romatic hearts click here

Submodel 1.Uniform specified polariser (no polariser gradient). Creating a shape using a specified pattern of isotropic growth. Result: simple patterns can readily produce blobby shapes.	<wikiflv width="300" height="300" logo="false" loop="true">GPT_TwoWayHeart_20110531-0001.flv|GPT_TwoWayHeart_20110531-0001_Last.png‎</wikiflv> Play submodel 1. Pattern of isotropic specified growth (no polariser)
Submodel 2.Uniform specified growth. Creating a shape using a specified pattern of diffusable polariser. Result: simple patterns can readily produce sharp shapes.	<wikiflv width="300" height="300" logo="false" loop="true">GPT_TwoWayHeart_20110531-0002.flv|GPT_TwoWayHeart_20110531-0002_Last.png‎</wikiflv> Play submodel 2. Pattern of specified polariser levels (green-cyan). Polariser can diffuse and the gradient is arrowed. Uniform specified growth (red).

3 Running models without the GUI

Having developed the concepts underpinning a pattern of growth in an interaction function it is often desirable to explore a range of model parameters. Given that each run of the model can take between 5 minutes and hour it is appropriate to run the models in parallel on a computing cluster. (Each node of the cluster to be used by GFtbox needs to be licensed to run Matlab - however for the purpose of running on a cluster without the GUI we are exploring the possibility of making GFtbox compatible with Octave.)