====== Module 1: Delta-Notch (ODE systems, ODEs on a grid) ======
Author: Fabian Rost
===== Aim =====
* learn about ODE models (dynamics in morpheus, steady states analytically)
* develop first models
===== Description =====
==== Basic ODEs ====
* get to know what students know about ODEs and adjust the module to the pre-knowledge
* give them very simple sketches of biomolecular models, which they should translate into ODEs, e.g.
digraph finite_state_machine {
rankdir=LR;
size="9,5"
node [shape = circle];
a[label="", fixedsize="false", width=0, height=0, shape=none];
a -> A [ label = "k1" ];
}
digraph finite_state_machine {
rankdir=LR;
size="9,5"
node [shape = circle];
A -> A [ label = "k2" ];
}
digraph finite_state_machine {
rankdir=LR;
size="9,5"
node [shape = circle];
a[label="", fixedsize="false", width=0, height=0, shape=none];
A -> a [ label = "k3" ];
}
digraph finite_state_machine {
rankdir=LR;
size="9,5"
node [shape = circle];
a[label="", fixedsize="false", width=0, height=0, shape=none];
b[label="", fixedsize="false", width=0, height=0, shape=none];
b -> A [ label = "k4" ];
A -> a [ label = "k5" ];
}
* could be translated to the following ODEs:
\begin{align}
\dot A &= k_1 \\
\dot A &= k_2 A \\
\dot A &= - k_3 A \\
\dot A &= k_4 - k_5 A
\end{align}
* discuss those ODEs by
* calculate steady state (do not calculate the stability, to complicated for biologists)
* simulate in morpheus
* typical models for biochemistry/systems biology use hill kinetics:
digraph {
size="9,5"
node [shape = circle];
a[label="", fixedsize="false", width=0, height=0, shape=none];
ab[label="", fixedsize="false", width=0, height=0, shape=none];
c[label="", fixedsize="false", width=0, height=0, shape=none];
a -> ab[arrowhead=None];
ab -> A;
A -> c
B -> ab[arrowhead=tee];
{rank=same; a; ab; A; c};
}
\begin{align}
\dot A &= \frac{\theta^n}{\theta^n + B^n} - k A
\end{align}
==== Delta-Notch ====
* then discuss the delta-notch sketch with two species
* start with the Collier model
* let them simplify the Collier model sketch (remove the delta or notch species)
* let them develop an ODE for this system (they should be able to do so from the above examples)
* they could come up with something like:
\begin{align}
\dot A_1 &= \frac{\theta^n}{\theta^n + A_2^n} - A_1 \\
\dot A_2 &= \frac{\theta^n}{\theta^n + A_1^n} - A_2
\end{align}
* this system is bistable for certain parameter ranges, if the students are advanced they might find this out themselves
* bistable e.g. for $\theta=0.5$, $n=4$,
* if they have this system running in morpheus go spatial and let them simulate the system on a square and hexagonal grid
* then you could also move to shaped cpm cells or even moving cells
* students won't do so much on their own in this session, it is a lot teaching on ODEs (don't be theoretical here, not enough time!) and introducing morpheus
Paper:
* Joanne R. Collier, Nicholas A.M. Monk, Philip K. Maini, Julian H. Lewis, Pattern Formation by Lateral Inhibition with Feedback: a Mathematical Model of Delta-Notch Intercellular Signalling, Journal of Theoretical Biology, Volume 183, Issue 4, 21 December 1996, Pages 429-446, ISSN 0022-5193, http://dx.doi.org/10.1006/jtbi.1996.0233.
===== Morpheus models =====
1k1 * A1theta^n / (theta^n + A_neighbour^n)
- k * Atheta^n / (theta^n + A^n)
- k * A_neighbour1theta^n/(theta^n+X_neighbour^2)
- Xrand_uni(0, 0.01)