Behavioural Modelling of Drugs Metabolism

A Joint Project of

IBM Italy

Department of Mathematics and Computer Science of Camerino

Department of Computer Science of Florence

Main investigators: 
Pietro Leo, IBM Italia S.p.A.
Rocco De Nicola, ... Dipartimento di Sistemi e Informatica, Universita` degli Studi di Firenze 
Flavio Corradini e CoSy members, Dipartimento di Matematica e Informatica, Università di Camerino

 

IBM-UNICAM-UNIFI team is exploring a formal and behavioural modelling for the prediction of the metabolism of drugs molecules.

We consider a biological system as a set of active components interacting in a dynamic and sometime unpredictable environment. The prediction will be based on behavioural modelling of molecular interactions. 
Such approach permits a natural, modular, extensible,  compositional representation and simulation of biological  systems, that goes beyond the classical differential equation based approach to Systems Biology.  
Since Process Algebra is the theory of equivalence of  computationl behaviours, we intend to apply models and  computational results obtained in the Formal Methods research area of Computer Science to this emerging area of  modern biology, with a particular attention to health-care applications (unknown drugs metabolism, personalized medicine).

 In particular, we propose to:
1. investigate on the appropriate computational  behavioural formalism and level of abstraction (e.g. PI Calculus and Process Algebra [12], Multi Agent System [2], Semantic Networks[3]) to adopt in the description of metabolic pathways of drugs

2. describe from the behavioural point of view the metabolic pathways of well-known molecules (drugs) both at graphic - e.g. automata, statecharts [11,13] - and/or textual level - process algebras - by using TAPAs or IBM tools.

3. verify the model properties (correct behavior = reachability; free of unwanted behaviors = safety; 
warrantee of correct behavior for any input = liveness) by using automatic tools [8,9] or IBM tools.

4. predict the (behavioural) metabolic pathways of unknown molecules (drugs) by exploiting the metabolic pathways of their structural homologues

 5. analyze the interactions between different metabolic pathways as a basis to study the drugs interferences

 6. represent in the model the personalized genetic context (i.e. gene polymorphisms, SNPs, etc.) which lead to personalized metabolism

7. apply tecniques and results obtained in the Formal Methods area to the metabolic and genetic behavioural  models developed

At the present, the Unicam and Unifi laboratories consist of

References:

[1] Regev, A., Shapiro, E.: Cellular abstractions: Cells as computation. Nature 419 (2002) 

[2] N. Cannata, F. Corradini, E. Merelli, A. Omicini, and A Ricci. An agent-oriented conceptual framework for systems biology. Transactions on Computational Systems Biology III, LNBI 3737, 2005. 

[3] Michael Hsing, Joel L Bellenson, Conor Shankey and Artem Cherkasov. Modeling of cell signaling pathways in macrophages by semantic networks. BMC Bioinformatics 2004, 5:156 

[4] N. Cannata, F. Corradini, E. Merelli. Multiagent modelling and simulation of carbohydrate oxidation International Journal of Modelling, Identification and Control (IJMIC) ISSN: 1746- 6172, 2006 (in stampa)

[5] E. Merelli, M. Young. Validating MAS with mutation International Journal of Multiagent and Grid Systems IOS Press, ISSN 1574-1702, 2006 (in stampa)

[6] N. Cannata, F. Corradini, E. Merelli. A Resourceomic Grid for Bioinformatics. International Journal of Grid Computing: Theory, Methods and Applications: Future Generation Computer Systems Journal ISSN: 0167-739X (accepted for publication)

[7] E. Merelli et al. Agents in Bioinformatics, Computational and Systems Biology. Briefings in Bioinformatics, 2006 (in stampa)

[8] R. Alur, C. Courcoubetis, D. L. Dill. Model-checking in dense real-time. Information and Computation 104:2-34, 1993.

[9] Cleaveland, R., Parrow, J. and Steffen, B. The Concurrency workbench: A semantics-based tool for the verification of concurrent system. ACM Trans Prog. Lang. System, 15: 36-72, 1993

[10] Hucka M et al. SBML Forum. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics, 19(4):524-31, 2003.

[11] Harel D., "Statecharts: A Visual Formalism for Complex Systems," Sci. Computer Prog., July 1987, pp. 231-274

[12] R. Milner. Communication and Concurrency. International series in Computer Science, Prentice Hall International, 1989

[13] Lüttgen G., von der Beeck M., Cleaveland R. Statecharts Via Process Algebra. CONCUR 1999: 399-414

 

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