Model Checking the Biological Model of Membrane Computing with Probabilistic Symbolic Model Checker by Using Two Biological Systems

Muniyandi,

doi:10.3844/jcssp.2010.669.678

Cited by 6 publications

(2 citation statements)

References 24 publications

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“…Membrane computing is a theoretical paradigm that abstracts from the structure and functionality of the living cell to create models and simulators of cellular phenomena (Muniyandi et al, 2010); hence, it produces formal specifications defined in a language that are close to molecular biology and returns meaningful and easily interpreted information to biologists (Muniyandi and Zin, 2011).…”

Section: Introductionmentioning

confidence: 99%

Implementing Mitogen Activated Protein Kinases Cascade on Membrane Computing Using P-Lingua

Shaalan¹,

Muniyandi

2015

Journal of Computer Science

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Abstract:The Mitogen Activated Protein Kinases (MAPK) cascade has been used as a case study for different computational software tools in both modelling and simulation of real-life problems. This study focuses on the development of new techniques for solving a MAPK cascade by using membrane computing. Membrane computing is an unconventional computational approach that provides a platform for modelling discrete system. This approach deals with parallel, distributed and non-deterministic computing models. P-Lingua is used to specify and analyze a wide range of quantitative properties and to offer a general syntactic framework that could be a formal standard for membrane computing. The model is simulated by using MeCoSim, a membrane computing simulator used to verify and validate the model. This study aimed to compare the use of the membrane computing approach for modelling the MAPK cascade with other models. The MAPK cascade, which is specified in P Lingua evaluated based on the simulation with MeCoSim. In general, we can say that the membrane computing model is better than previous models because it takes into account the changes that occur in the cell and because the problem is mainly a problem in the cells; therefore the model achieves the best results and reliability.

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Section: Introductionmentioning

confidence: 99%

Implementing Mitogen Activated Protein Kinases Cascade on Membrane Computing Using P-Lingua

Shaalan¹,

Muniyandi

2015

Journal of Computer Science

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“…There are many model checking systems which are developed; the most popular are SMV (McMillan, 1999;Islam et al, 2010), UPPAAL (Bengtsson et al, 1995;El Emary and Al Rabia, 2005), SPIN (Holzmann, 2003) and PRISM (Marta, 2003, Chandren et al, 2010. Each of the model checkers comes in a package with its own input language which has strict notations and features (Bhaduri and Ramesh, 2004;Djavanroodi et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Model Checkers' Input Languages for Modeling Traffic Light Systems

Samat

Zin

Shukur

2011

Journal of Computer Science

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Problem statement: Model checking is an automated verification technique that can be used for verifying properties of a system. A number of model checking systems have been developed over the last few years. However, there is no guideline that is available for selecting the most suitable model checker to be used to model a particular system. Approach: In this study, we compare the use of four model checkers: SMV, SPIN, UPPAAL and PRISM for modeling a distributed control system. In particular, we are looking at the capabilities of the input languages of these model checkers for modeling this type of system. Limitations and differences of their input language are compared and analyses by using a set of questions. Results: The result of the study shows that although the input languages of these model checkers have a lot of similarities, they also have a significant number of differences. The result of the study also shows that one model checker may be more suitable than others for verifying this type of systems Conclusion: User need to choose the right model checker for the problem to be verified.

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Simulation Strategy of Membrane Computing to Characterize the Structure and Non-deterministic Behavior of Biological Systems: A Case Study with Ligand-Receptor Network of Protein TGF-β

Muniyandi

Abdullah

2011

Lecture Notes in Computer Science

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Model Checking the Biological Model of Membrane Computing with Probabilistic Symbolic Model Checker by Using Two Biological Systems

Cited by 6 publications

References 24 publications

Implementing Mitogen Activated Protein Kinases Cascade on Membrane Computing Using P-Lingua

Implementing Mitogen Activated Protein Kinases Cascade on Membrane Computing Using P-Lingua

Analysis of the Model Checkers' Input Languages for Modeling Traffic Light Systems

Simulation Strategy of Membrane Computing to Characterize the Structure and Non-deterministic Behavior of Biological Systems: A Case Study with Ligand-Receptor Network of Protein TGF-β

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