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Agent-based model, biological cell, chemical reaction model, motifs, simulation, Tools
We describe a multiset of agents based modeling and simulation paradigm for synthetic biology. The multiset of agents –based programming paradigm, can be interpreted as the outcome arising out of deterministic, nondeterministic or stochastic interaction among elements in a multiset object space, that includes the environment. These interactions are like chemical reactions and the evolution of the multiset can emulate the system biological functions. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of elements, so that the elements evolve toward equilibrium or emergent state. Practical realization of this paradigm for system biological simulation is achieved through the concept of transactional style programming with agents, as well as soft computing (neural- network) principles. Also we briefly describe currently available tools for agent-based-modeling, simulation and animation.
E.V.Krishnamurthy, "Agent-based Models in Synthetic Biology: Tools for Simulation and Prospects", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.2, pp.58-65, 2012. DOI:10.5815/ijisa.2012.02.07
Adamsky,A and Komosinski,M. (2006), Artificial life Models in Software, Springer, New York.
Alberts,B et al. (2002),The Molecular Biology of the Cell, Garland Science, New York.
Alon, U. (2000), An Introduction to Systems Biology, Chapman and Hall, London.
Aviv,R and Shapiro,E.(2002) Cellular Abstractors: Cellular computation, Nature, Vol 419, 343.
Boloni,L et al (2004) Software Engineering Challenges for mutable-agent systems, Lecture Notes in Computer Science, Vol.2940,pp.149-166, Springer Verlag, New York.
Cardelli,L. (2005) Abstract Machines in Systems Biology, Springer Transactions on Biological Systems, Springer Verlag, New York.
Clark, D.P., and Russell,L.D., Molecular Biology, Cache River Press, Vienna, Ill.,1997
Effroni,S et al. (2005) Reactive animation: Realistic Modeling of Complex Dynamic Systems, IEEE Computer, January, 33-46.
Goldberg,D.E..(1989) Genetic algorithms in search, optimisation and machine learning, Addison Wesley, Reading, Mass.
Gorton,I. (2004) Evaluating agent Architectures: Cougaar, Aglets and AAA, Lecture Notes in Computer Science,Vol.2940, Springer Verlag, New York,264-274.
Harel,D.(2003) A grand challenge for computing: towards full reactive modeling of a multicellular animal, EATCS Bulletin, http:// www. wisdom.weizmann.ac.il/ ~dharel / papers/grandchallenge.doc.
Jacob,C. and Burleigh,I., Biomolecular swarms-an agent based model of the lactose operon, Natural computing, Vol. 3,pp.361-376, 2004.
Jacob,C, Barbasiewicz,A,and.Tsui,G, Swarms and Genes : Exploring Lambda switch gene regulation thro Swarm intelligence, Proc. IEEE congress on Evolutionary Computation, 2006, Vancouver.
Keele,J.W and Wray, J.E. (2005). Software Agents in molecular computational Biology, Briefings in Bioinformatics, Vol.6, No.5,December, 370-379.
Koza,J.R (1999) Genetic programming III, Morgan Kaufmann, San Francisco.
Krishnamurthy, E.V. and Murthy, V.K(1991) Transaction Processing, Prentice Hall, N.J
Lauffenburger,D.A.and Linderman,J.L. (1993) Receptors, Oxford University Press, Oxford.
Lucena, C et al.(2004) Software Engineering for Multi-agent Systems, Lecture Notes in Computer Science, Vol.2940, Springer Verlag, New York.
Murthy, V.K and Krishnamurthy, E.V (2009)," Multiset of Agents in a Network for Simulation of Complex Systems", in Recent advances in Nonlinear Dynamics and synchronization (NDS-1) -Theory and applications, Springer Verlag, New York, 2009. Eds. K.Kyamakya et al.
North, M.J and Burton, E.J.,(2006), Escaping the accidents of History: An overview of Artificial life modelling with Repast, in , 115-142.
Odell,J.J,Objects and agents compared, J. Object technology,(2002) Vol.1, 41-53,May-June.
Pinney,J.W et al. (2003) Petri net representations in systems biology, Biochemical Society Transactions,Vol.31, Pt 6.
Sekanina,L. (2005),Evolvable components,Springer, New York.
Shakshuki,E and Jun,Y(2004) Multi-agent development toolkits: An Evaluation, Lecture Notes in Artificial intelligence, 3029, Springer Verlag, New York, 209-218.
Stith, B.J. (2004) Use of animation in teaching cell biology, Cell. Biology Education, Vol.3(3),Fall,181-188.
Thomas ,R and, D’Ari,R, Biological feedback, CRC Press, Boca Raton, Florida, 1990.
Vallurpalli,V and Purdy,C Agent based modeling and simulation of biomolecular reactions, Univ. of Cincinnati, 2006.
Watson,J.D et al, Molecular biology of the Gene, Benjamin Cummings, San Francisco , 2008.
Wooley,J.C and.Lin,H.C. (Eds.) (2005) Catalyzing inquiry at the interface of computing and biology, National Academies Press, Washington, DC.
Woolridge,M(2002) Introduction to Multi-Agent systems, John Wiley, New York.