An automated approach to translate a biological process from ODEs into graphical hybrid functional Petri Nets

Imene Mecheter, Rachid Hadjidj, Sebti Foufou

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The study of biological systems is growing rapidly, and can be considered as an intrinsic task in biological research, and a prerequisite for diagnosing diseases and drug development. The integration of biological studies with computer technologies led to noticeable developments in biology with the appearance of many powerful modeling and simulation techniques and tools. The help of computers in biology resulted in deeper knowledge about complex biological systems and biopathways behaviors. Among modeling tools, the Petri Net formalism plays an important role. Petri Net is a powerful computerized and graphical modeling technique originally developed by Carl Adam Petri in 1960 to model discrete event systems. With its various extensions, Petri Nets find applications in many other fields including Biology. The extension known under the name Hybrid Functional Petri Net (HFPN) was developed specifically to model biological systems. Traditionally, biological processes are captured as systems of ordinary differential equations (ODEs). However, HFPNs offer a much more elegant and versatile approach to represent these processes more accurately. In fact, HFPNs allow to capture phenomena which are impossible to capture with ODES, while being more intuitive and easy to understand and model with. In this work we propose an approach to translate a system of ODEs representing a biological process into a HFPN. The resulting HFPN, not only preserves the semantics of the original model, but is also more humanly readable thanks to the use of a novel technique to connect its components in a smart way. To validate our approach, we implemented it as an extension to the tool Real Time Studio (an integrated environment for modeling, simulation and automatic verification of real-time systems), and compared our simulation results with those obtained by simulating systems of ODEs using MATLAB.

    Original languageEnglish (US)
    Title of host publication2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781467389884
    DOIs
    StatePublished - Oct 4 2017
    Event2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017 - Manchester, United Kingdom
    Duration: Aug 23 2017Aug 25 2017

    Other

    Other2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017
    CountryUnited Kingdom
    CityManchester
    Period8/23/178/25/17

    Fingerprint

    Biological Phenomena
    Petri nets
    Ordinary differential equations
    Petri Nets
    Ordinary differential equation
    Biological systems
    System of Ordinary Differential Equations
    Biological Systems
    Biology
    Biological Models
    Computer Systems
    Semantics
    Names
    Modeling and Simulation
    Biological Sciences
    Technology
    Graphical Modeling
    Automatic Verification
    Computer Technology
    Discrete Event Systems

    ASJC Scopus subject areas

    • Computational Mathematics
    • Modeling and Simulation
    • Health Informatics
    • Agricultural and Biological Sciences (miscellaneous)
    • Artificial Intelligence
    • Computer Science Applications
    • Computer Vision and Pattern Recognition

    Cite this

    Mecheter, I., Hadjidj, R., & Foufou, S. (2017). An automated approach to translate a biological process from ODEs into graphical hybrid functional Petri Nets. In 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017 [8058558] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIBCB.2017.8058558

    An automated approach to translate a biological process from ODEs into graphical hybrid functional Petri Nets. / Mecheter, Imene; Hadjidj, Rachid; Foufou, Sebti.

    2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8058558.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Mecheter, I, Hadjidj, R & Foufou, S 2017, An automated approach to translate a biological process from ODEs into graphical hybrid functional Petri Nets. in 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017., 8058558, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017, Manchester, United Kingdom, 8/23/17. https://doi.org/10.1109/CIBCB.2017.8058558
    Mecheter I, Hadjidj R, Foufou S. An automated approach to translate a biological process from ODEs into graphical hybrid functional Petri Nets. In 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 8058558 https://doi.org/10.1109/CIBCB.2017.8058558
    Mecheter, Imene ; Hadjidj, Rachid ; Foufou, Sebti. / An automated approach to translate a biological process from ODEs into graphical hybrid functional Petri Nets. 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
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