Team:Dundee/Modeling/netlogo

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NetLogo is “an agent-based programming language and integrated modelling environment” and we used it to develop simulations to see the effects of space within the cell for the PQS and BDSF systems.  NetLogo is an easy-to-implement tool and is part of the class of individual-based models (IBMs). The video below is an example run of the one of the PQS simulations.   
NetLogo is “an agent-based programming language and integrated modelling environment” and we used it to develop simulations to see the effects of space within the cell for the PQS and BDSF systems.  NetLogo is an easy-to-implement tool and is part of the class of individual-based models (IBMs). The video below is an example run of the one of the PQS simulations.   
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<video controls="controls"  name="PQS_NetLogo" src="https://static.igem.org/mediawiki/2014/8/8c/High_promoters_converted.mov"></video>
<video controls="controls"  name="PQS_NetLogo" src="https://static.igem.org/mediawiki/2014/8/8c/High_promoters_converted.mov"></video>
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We discuss the results pertaining to the PQS system.  Similar results were obtained for the other systems. The NetLogo model represents a cross-section of our E.coli chassis.  
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We discuss the results pertaining to the PQS system.  Similar results were obtained for the other systems. The NetLogo model represents a cross-section of our <i>E. coli</i> chassis.  
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The spatially extended stochastic simulations generated by NetLogo  exhibited broadly similar general trends as predicted by the other mathematical tools that we used.  For example in Fig 1. we can see that increasing the number of signalling molecules increases the number of fluorescent molecules produced.  Although we could not achieve close quantitative  agreement with our other predictions, NetLogo did allow us to better visualise the effects of changing the number of signalling molecules, receptors and promoters on the expression of mCherry.  
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The spatially extended stochastic simulations generated by NetLogo  exhibited broadly similar general trends as predicted by the other mathematical tools that we used.  For example in Fig 1, we can see that increasing the number of signalling molecules increases the number of fluorescent molecules produced.  Although we could not achieve close quantitative  agreement with our other predictions, NetLogo did allow us to better visualise the effects of changing the number of signalling molecules, receptors and promoters on the expression of mCherry.  
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Since our project focuses strongly on public engagement, we realised that we would need to have a clear, non-technical and most importantly, interactive  method of explaining the science of the project  to potential users of The Lung Ranger/L.A.S.S.O. and wider public public. The NetLogo simulations provided a really useful visual aid for explaining how the biological systems worked.  For instance, when we presented our project at the UK Cystic Fibrosis Trust Conference our audience included clinicians, patients and parents. The feedback received afterwards highlighted that the science had been understood because of the NetLogo animation.
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Since our project focuses strongly on public engagement, we realised that we would need to have a clear, non-technical and, most importantly, interactive  method of explaining the science of the project  to potential users of The Lung Ranger/L.A.S.S.O. and wider public. The NetLogo simulations provided a really useful visual aid for explaining how the biological systems worked.  For instance, when we presented our project at the UK Cystic Fibrosis Trust Conference our audience included clinicians, patients and parents. The feedback received afterwards highlighted that the science had been understood because of the NetLogo animation.
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Latest revision as of 23:43, 17 October 2014

Dundee 2014

NetLogo

Modelling Comes to Life

Introduction

NetLogo is “an agent-based programming language and integrated modelling environment” and we used it to develop simulations to see the effects of space within the cell for the PQS and BDSF systems. NetLogo is an easy-to-implement tool and is part of the class of individual-based models (IBMs). The video below is an example run of the one of the PQS simulations.


Objectives

We wished to use the NetLogo IBM for two main purposes: (i) an investigation of potential intracellular spatial effects in the signalling pathways and (ii) the development of an easily accessible graphical user interface for the modelling component of the project.


Intracellular Spatial Effects

We discuss the results pertaining to the PQS system. Similar results were obtained for the other systems. The NetLogo model represents a cross-section of our E. coli chassis.



The spatially extended stochastic simulations generated by NetLogo exhibited broadly similar general trends as predicted by the other mathematical tools that we used. For example in Fig 1, we can see that increasing the number of signalling molecules increases the number of fluorescent molecules produced. Although we could not achieve close quantitative agreement with our other predictions, NetLogo did allow us to better visualise the effects of changing the number of signalling molecules, receptors and promoters on the expression of mCherry.


Graphical User Interface - Modelling Comes to Life

Since our project focuses strongly on public engagement, we realised that we would need to have a clear, non-technical and, most importantly, interactive method of explaining the science of the project to potential users of The Lung Ranger/L.A.S.S.O. and wider public. The NetLogo simulations provided a really useful visual aid for explaining how the biological systems worked. For instance, when we presented our project at the UK Cystic Fibrosis Trust Conference our audience included clinicians, patients and parents. The feedback received afterwards highlighted that the science had been understood because of the NetLogo animation.


Conclusion

NetLogo provided a good qualitative comparison with the ODE and SSA models indicating that intracellular spatial effects were sufficiently captured on average by the more quantitative ODE/SSA approaches. Future work would include the development of our model into a 3D simulation so we could more fully study these intracellular spatial effects. The most striking and useful aspect of this software was its ability to take the science, modelling and project as a whole into the hands of users.