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A Steering Server for Collaborative Simulation of Quantitative Petri - - PowerPoint PPT Presentation

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Interacting with S 4 Introduction Architecture Use Case Conclusion A Steering Server for Collaborative Simulation of Quantitative Petri Nets Mostafa Herajy 1 and Monika Heiner 2 Department of Mathematics and Computer Science, Faculty of

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SLIDE 1

Introduction Interacting with S4 Architecture Use Case Conclusion

A Steering Server for Collaborative Simulation

  • f Quantitative Petri Nets

Mostafa Herajy 1 and Monika Heiner 2

Department of Mathematics and Computer Science, Faculty of Science, Port Said University - Port Said, Egypt Computer Science Institute, Brandenburg University of Technology Cottbus, Germany

Tunis 2014

  • M. Herajy and M. Heiner 2014

Snoopy Steering and Simulation Server - S4 1 / 21

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Introduction Interacting with S4 Architecture Use Case Conclusion

Agenda

1 Introduction 2 Interacting with S4 3 Architecture 4 Use Case 5 Conclusion

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Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

  • M. Herajy and M. Heiner 2014

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SLIDE 4

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

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SLIDE 5

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

  • M. Herajy and M. Heiner 2014

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SLIDE 6

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

  • M. Herajy and M. Heiner 2014

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SLIDE 7

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation

  • M. Herajy and M. Heiner 2014

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SLIDE 8

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation Execution

Simulation

  • M. Herajy and M. Heiner 2014

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SLIDE 9

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation Execution

Simulation

Monitoring

2 4 6 8 10 12 14 16 18 100 200 300 400 500 600 700 800 900 1000 number of molecules time stochastic hybrid continuous

Results

  • M. Herajy and M. Heiner 2014

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SLIDE 10

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation Execution

Simulation

Monitoring

2 4 6 8 10 12 14 16 18 100 200 300 400 500 600 700 800 900 1000 number of molecules time stochastic hybrid continuous

Results Users

Interpretation

  • M. Herajy and M. Heiner 2014

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SLIDE 11

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation Execution

Simulation

Monitoring

2 4 6 8 10 12 14 16 18 100 200 300 400 500 600 700 800 900 1000 number of molecules time stochastic hybrid continuous

Results Users

Interpretation

✬ ✫ ✩ ✪

  • M. Herajy and M. Heiner 2014

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SLIDE 12

Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation Execution

Simulation

Monitoring

2 4 6 8 10 12 14 16 18 100 200 300 400 500 600 700 800 900 1000 number of molecules time stochastic hybrid continuous

Results Users

Interpretation

✬ ✫ ✩ ✪

Steering

Intermediate

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

Modelling of Biochemical Reaction Networks

Biological Phenomenon

Understanding

Diagrammatic Description

Formulation

ODEs

Representation

!"# !"#$%! !"#$! & '( ! '( )"# '( )% )* )+ ), )- ). )/ )'( )' )0 % %

Petri nets

Formulation/Representation Execution

Simulation

Monitoring

2 4 6 8 10 12 14 16 18 100 200 300 400 500 600 700 800 900 1000 number of molecules time stochastic hybrid continuous

Results Users

Interpretation

✬ ✫ ✩ ✪

Steering

Intermediate

✬ ✫ ✩ ✪

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Motivations

Currently existing Petri net tools focus on facilitating model constructions, but pay little attention to simulation features. Certain biological models require sophisticated simulation environments during model execution. Utilize the computational power of high performance computers. The need to reduce the overall required time to run an experiment. The need to promote knowledge sharing between different users.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Motivations

Currently existing Petri net tools focus on facilitating model constructions, but pay little attention to simulation features. Certain biological models require sophisticated simulation environments during model execution. Utilize the computational power of high performance computers. The need to reduce the overall required time to run an experiment. The need to promote knowledge sharing between different users.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Motivations

Currently existing Petri net tools focus on facilitating model constructions, but pay little attention to simulation features. Certain biological models require sophisticated simulation environments during model execution. Utilize the computational power of high performance computers. The need to reduce the overall required time to run an experiment. The need to promote knowledge sharing between different users.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Motivations

Currently existing Petri net tools focus on facilitating model constructions, but pay little attention to simulation features. Certain biological models require sophisticated simulation environments during model execution. Utilize the computational power of high performance computers. The need to reduce the overall required time to run an experiment. The need to promote knowledge sharing between different users.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Motivations

Currently existing Petri net tools focus on facilitating model constructions, but pay little attention to simulation features. Certain biological models require sophisticated simulation environments during model execution. Utilize the computational power of high performance computers. The need to reduce the overall required time to run an experiment. The need to promote knowledge sharing between different users.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features

Remotely run and control a simulation. Execution of one model using different simulation algorithms. Managing different models concurrently with possibly different simulators. Defining different views to explore simulation results. Exploring the running models on-the-fly.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features

Remotely run and control a simulation. Execution of one model using different simulation algorithms. Managing different models concurrently with possibly different simulators. Defining different views to explore simulation results. Exploring the running models on-the-fly.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features

Remotely run and control a simulation. Execution of one model using different simulation algorithms. Managing different models concurrently with possibly different simulators. Defining different views to explore simulation results. Exploring the running models on-the-fly.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features

Remotely run and control a simulation. Execution of one model using different simulation algorithms. Managing different models concurrently with possibly different simulators. Defining different views to explore simulation results. Exploring the running models on-the-fly.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features

Remotely run and control a simulation. Execution of one model using different simulation algorithms. Managing different models concurrently with possibly different simulators. Defining different views to explore simulation results. Exploring the running models on-the-fly.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features (Cont.)

Steering simulation parameters while a simulation is running. Controlling the simulation speed. Connecting to a simulation at any time from whatever place. Collaborating with other people while simulating a model. Platform-independent implementation.

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features (Cont.)

Steering simulation parameters while a simulation is running. Controlling the simulation speed. Connecting to a simulation at any time from whatever place. Collaborating with other people while simulating a model. Platform-independent implementation.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features (Cont.)

Steering simulation parameters while a simulation is running. Controlling the simulation speed. Connecting to a simulation at any time from whatever place. Collaborating with other people while simulating a model. Platform-independent implementation.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features (Cont.)

Steering simulation parameters while a simulation is running. Controlling the simulation speed. Connecting to a simulation at any time from whatever place. Collaborating with other people while simulating a model. Platform-independent implementation.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

S4– Features (Cont.)

Steering simulation parameters while a simulation is running. Controlling the simulation speed. Connecting to a simulation at any time from whatever place. Collaborating with other people while simulating a model. Platform-independent implementation.

  • M. Herajy and M. Heiner 2014

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Introduction Interacting with S4 Architecture Use Case Conclusion

Model Definition

We can define a model via: Snoopy Application Programming Interface

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Introduction Interacting with S4 Architecture Use Case Conclusion

Model Definition via Snoopy1

1Heiner et al. 2012

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Introduction Interacting with S4 Architecture Use Case Conclusion

Model Definition via API

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Introduction Interacting with S4 Architecture Use Case Conclusion

Model Definition via API (Cont.)

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Introduction Interacting with S4 Architecture Use Case Conclusion

Model Exploration

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Introduction Interacting with S4 Architecture Use Case Conclusion

Monitoring and Steering

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Introduction Interacting with S4 Architecture Use Case Conclusion

Supported Petri Net Classes 2

time-free timed, quantitative discrete state space continuous state space QPN C QPN SPN C SPN CPN C CPN GHPN C GHPN molecules/levels LTS, PO CTL/LTL molecules/levels stochastic rates CTMC CSL/PLTLc concentrations deterministic rates ODEs LTLc folding unfolding abstraction extension approximation molecules and concentrations stochastic and deterministic rates CTMC coupled by Markov jumps PLTLc

2Heiner et al. 2012

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Introduction Interacting with S4 Architecture Use Case Conclusion

Architecture

External Simulator 1 External Simulator 2 External Simulator N

Change parameters Result output

PN definition Result Views Model 1 Internal Simulator

Change Result Visualization

External simulator (optional) Steering Server Users

Change parameters Result output Change parameters Result output User 1 User 2 User M Steering Visualization Steering Steering Visualization Visualization Steering

Steering Application Programming Interface Steering Application Programming Interface

PN definition Result Views Model 2 Internal Simulator

Change Result

PN definition Result Views Model N Internal Simulator

Change Result

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Introduction Interacting with S4 Architecture Use Case Conclusion

Available Simulators3

  • 3M. Herajy and M. Heiner 2012
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Introduction Interacting with S4 Architecture Use Case Conclusion

Use Case

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Introduction Interacting with S4 Architecture Use Case Conclusion

Circadian Oscillation

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Introduction Interacting with S4 Architecture Use Case Conclusion

Circadian Oscillation

G1 0.2 G2_active 9 G1_active 9 A A G2 0.2 mRNA_G1 A_R R mRNA_G2 R1 R2 R3 R4 R9 R10 R8 R11 R12 R16 R18 R17 R7 R6 R5 R14 R15 R13 k1 50 k3 100 k5 500 k7 10 k9 50 k11 1 k13 50 k2 1 k4 1 k6 50 k8 50 k10 100 k12 2 k14 0.01 k16 5 k15 0.5 k17 0.2 k18 1

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Introduction Interacting with S4 Architecture Use Case Conclusion

Circadian Oscillation (Cont.)

2000 4000 6000 8000 10000 12000 14000 16000 18000 100 200 300 400 500 concentration time

Without S4

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Introduction Interacting with S4 Architecture Use Case Conclusion

Circadian Oscillation (Cont.)

2000 4000 6000 8000 10000 12000 14000 16000 18000 100 200 300 400 500 concentration time

Without S4

5000 10000 15000 20000 25000 100 200 300 400 500 concentration time

With S4

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Introduction Interacting with S4 Architecture Use Case Conclusion

Live Demo using S4

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Introduction Interacting with S4 Architecture Use Case Conclusion

For More Information:

Visit our website: http://www-dssz.informatik. tu-cottbus.de/DSSZ/Software/Snoopy S4 user manual Join us at the Tools Exhibition, Thursday 13:30

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Introduction Interacting with S4 Architecture Use Case Conclusion

Thank You

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