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