Abstract
The concepts promotion and inhibition are commonly used to explain the effects of interactions. These concepts are used with inference rules among them, such as “X inhibits Y, and Y promotes Z, therefore X inhibits Z.” Even when considering highly complex systems such as biological processes, many experimental facts can be explained using a few critical chains of reactions and their promotion/inhibition effects. The overall interaction effect of paths can be determined by considering relative properties, for example when an interaction effect of certain paths is stronger than that of others. In this paper, we present a formal ontology of interactions by providing a set of rules for the quantitative relations of the interaction effects of paths. Quantitative relations can be used to infer the overall interaction effect of all paths in a reaction network. Additionally, we present denotational semantics based on mass action kinetics with linear approximation at a steady state and prove the soundness of the given rules.
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References
The Systems Biology Markup Language, http://sbml.org/
Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.: Gene ontology: tool for the unification of biology. Nature Genetics 25(1), 25–29 (2000)
Bergstra, J.A.: Handbook of Process Algebra. Elsevier Science Inc. (2001)
Calder, M., Vyshemirsky, V., Gilbert, D., Orton, R.: Analysis of signalling pathways using the prims model checker. In: Proceedings of Computational Methods in Systems Biology (CMSB 2005), pp. 179–190 (2005)
Clarke, E.M., Grumberg, O., Peled, D.A.: Model Checking. MIT Press (1999)
Emerson, E.A.: Temporal and modal logic. In: Handbook of Theoretical Computer Science, pp. 995–1072. Elsevier (1995)
Fages, F., Soliman, S.: Formal cell biology in biocham. In: Bernardo, M., Degano, P., Zavattaro, G. (eds.) SFM 2008. LNCS, vol. 5016, pp. 54–80. Springer, Heidelberg (2008)
Fages, F., Solimman, S., Chabrier-River, N.: Modelling and querying interaction networks in the biochemical abstract machine biocham. Journal of Biological Physics and Chemistry 4(2), 64–73 (2004)
NuSMV, http://nusmv.irst.itc.it/
Peterson, J.L.: Petri Net Theory and the Modeling of Systems. Prentice Hall PTR (1981)
SPIN, http://spinroot.com/
Tashima, K., Izumi, N., Yonezaki, N.: A quantitative semantics of formal ontology of drug interaction. In: BIOCOMP 2008, pp. 760–766 (2008)
Yonezaki, N., Izumi, N., Akiyama, T.: Formal ontology of object interaction. In: Proceedings of International Symposium on Large-scale Knowledge Resources, pp. 15–20 (2006)
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Tomita, T., Izumi, N., Hagihara, S., Yonezaki, N. (2013). A Formal Ontology of Interactions with Intensional Quantitative Semantics. In: Nishizaki, Sy., Numao, M., Caro, J., Suarez, M.T. (eds) Theory and Practice of Computation. Proceedings in Information and Communications Technology, vol 7. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54436-4_2
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DOI: https://doi.org/10.1007/978-4-431-54436-4_2
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-54435-7
Online ISBN: 978-4-431-54436-4
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