source: liacs/pnbm/project/report.tex@ 23

Last change on this file since 23 was 18, checked in by Rick van der Zwet, 15 years ago

Revised model

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2% $Id: report.tex 571 2008-04-20 17:31:04Z rick $
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4
5\documentclass[12pt,a4paper]{article}
6
7\frenchspacing
8\usepackage[english]{babel}
9\selectlanguage{english}
10\usepackage{graphicx}
11\usepackage{url}
12\usepackage{multicol}
13\usepackage{fancybox}
14\usepackage{amssymb,amsmath}
15
16\title{DRAFT: Modeling planar signalling in AP axis development in \emph{Xenopus laevis}\\
17\large{using Petri Nets in Higher Level Developmental Biology}}
18\author{Rick van der Zwet, Tiago Borges Coelho \\
19 \texttt{<hvdzwet@liacs.nl>,<borges.coelho@gmail.com>}\\
20 LIACS - Leiden University, The Netherlands}
21\date{\today}
22
23\begin{document}
24\maketitle
25\section{Abstract}
26Planar signaling is the process in which cells accumulate proteins based on the
27saturation of nearby cells. If one cell produces n ammount of proteins, it will
28initiate a transfering cascade to cells in the vicinity. This dissemination of
29proteins will eventually cease, considering that n is a finite variable. There
30is a gradation in the ammount of proteins transfered, meaning that neighbouring
31cells get n/2 the ammount of proteins of the most saturated cell.
32
33XXX: Citing to the Bio Papers
34XXX: Small introductions Petri-nets
35
36\section{Approch}
37First a PetriNet model will be defined textually and using graphs next the
38modeling will be taking into practice using the modeling tool\emph{CPNTools}.
39
40\section{Modeling}
41To model this process we will take a modular approach using coloured PetriNets
42(see Fig~\ref{fig:model}), since the goal of this assignment is to have a
43solution that can be applied to any configuration of cells. We start with a
44bulding block that is an abstraction of a cell (figure: circle), which can then
45be coupled to other cells (figure: arrows). The abstraction contains two
46different types. First the proteins are modelled (figure: red), secondly the
47proteins (figure: blue) are leading in a second process of the creation of
48gradients which also needs modeling. We assume a 1:1 mapping between the amount
49of proteins and gradients -this taken into consideration- ones an \texttt{INITIAL}
50protein is 'used' (e.g. has on posterisation counterpart) in this process it
51get called \texttt{ACTIVATED}. We assume that the proteins to posterisation
52process is taking place at the same time as the proteins distribution. And in a
53special format (figure: object B). It tries to matches the posterisation to the
54same level as the proteins present. But the moment the protein level lowers,
55the posterisation will remain the same. In pseudo-code:
56\begin{verbatim}
57if numPos < numProteins then
58 numPos = numPos + 1
59endif
60\end{verbatim}
61\texttt{numProteins} is the proteins available and \texttt{numPos} is the
62posterisation present.
63
64The connectors between the cells (the membrams) has a special properly. One
65can see them as pressure valves others as sighons (see Fig~\ref{fig:pressure}).
66The moment the 'volume' at complies with the following properly $A / 2 < B$
67then the pressure closes, else it passes volume from A to B at an certain rate
68(\texttt{flowSpeed}). This rate could depend on the difference, actual value present
69or something else.
70
71For the case there exists no standard PetriNet 'component', hence this require
72the creation of a new property (figure: $2:1$), with the following properties:
73
74\begin{verbatim}
75flowSpeed = n
76if A > 2 * B then
77 A = A - flowSpeed
78 B = B + flowSpeed
79else if B > 2 * A then
80 B = B - flowSpeed
81 A = A + flowSpeed
82endif
83\end{verbatim}
84
85Planar signaling could theoretically start in every cell, by
86inserting some amount of protiens. In our model represented as a bunch of
87\texttt{INITIAL} tokens beeing put in a random cell.
88
89\begin{figure}[htp]
90\centering
91\caption{Planar signaling model}
92\includegraphics[width=100mm]{planar-signaling-model.eps}
93\label{fig:model}
94\end{figure}
95
96\begin{figure}[htp]
97\centering
98\caption{Pressure valve example}
99\includegraphics[height=60mm]{pressure-valve.eps}
100\label{fig:pressure}
101\end{figure}
102
103\section{CPNTools 'implementation'}
104CPNTools has quite some shortcomings when it comes to modeling (higher level
105developmental) biology.
106
107One it the shortcoming of the 'balancing'. It does not allow reading of how
108many tokens are present in a certain state and base action uppon them. As
109workaround for this (see Fig~\ref{fig:CPNplanar}) we used a 'dump' gradation
110function. In our case it simply take 3 tokens and pushes 1 forward and
111converting 2 directly to \texttt{ACTIVATED}. This does not take in
112consideration if the amount get changed in 'further-up', by some external
113source.
114
115Secondly it is missing a possibility to for easy random initialisation for
116modeling purposes. As a dirty quirk we 'hacked' it to choose between starting
117at the head or the tail.
118
119In this implementation the protiens to gradiants process is taking place at
120cell $A$ at the same time that the proteins get transfered from cell $A$ to
121$B$.
122
123Also it should be noted that it missing a notion of timed firing sequences;
124meaning firing sequences which will occur at an certain time. This could for
125example used to 'trigger' a timmed activation of the \texttt{INITIAL} to
126\texttt{ACTIVATED} process as modeled in fig~\ref{fig:model}. An initial idea
127is shown at fig\ref{fig:time-idea} in appendix 1.
128
129
130\begin{figure}[htp]
131\centering
132\caption{CPNTools implementation}
133\advance\leftskip-2cm
134\advance\rightskip+2cm
135\includegraphics[width=1.3\textwidth]{planer-signaling.eps}
136\label{fig:CPNplanar}
137\end{figure}
138
139\section{Conclusion}
140Using PetriNets for modeling biology processes is a powerful framework, which
141could be well extendable. The Proof Of Concept implementations and
142visualisations how-ever are lacking. \emph{CPNTools} for example does not
143provide a powerfull enough toolset for the modeling purposes.
144
145\begin{thebibliography}{10}
146% sing Petri Nets in Higher Level Developmental Biology:
147% A case study on the AP axis development in Xenopus laevis
148% Extended Abstract
149% http://www.liacs.nl/~csbpn/COURSE%20DOCUMENTS/extended%20abstract%20Bertens%20Jansen%20Kleijn%20Koutny%20Verbeek.pdf
150% Laura M.F. Bertens
151
152% http://www.liacs.nl/~csbpn/
153%
154%
155
156\end{thebibliography}
157\section{*Appendix}
158
159\begin{figure}[htp]
160\centering
161\caption{Timed transition idea}
162\includegraphics[width=0.5\textwidth]{timer-proposal.eps}
163\label{fig:time-idea}
164\end{figure}
165\end{document}
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