Abstract
A major challenge in computational systems biology is the articulation of a biological process in a form which can be understood by the biologist yet is amenable to computational execution. Process calculi have proved to especially powerful computational tools for modelling and reasoning about biological processes and we have previously described, and implemented, a Narrative approach to describing biological models which is a biologically intuitive high level language that can be translated into executable process calculus programs. Here we discuss an extension to the narrative approach which attempts to directly link biological data with Narrative primitives by suggesting an equivalence relationship between a string (the amino acid sequence) and a process. We outline future challenges in applying this approach more generally.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Priami, C.: Algorithmic Systems Biology An Opportunity for Computer Science. Communications of the ACM 52, 80–88 (2009)
Kwiatkowska, M.Z., Heath, J.K.: Biological pathways as communicating computer systems. J. Cell Sci. (in press, 2009)
Fisher, J., Henzinger, T.A.: Executable cell biology. Nat. Biotechnol. 25(11), 1239–1249 (2007)
Hunt, C.A., Ropella, G.E., Park, S., Engeleberg, J.: Dichotomies between computational and mathematical models. Nature Biotechnology 26, 737–738 (2008)
Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes, Pts 1 and 2. Information and computation 100(11), 1–40 (1992) (print)
Regev, A., Silverman, W., Shapiro, E.: Representation and simulation of biochemical processes using the pi-calculus process algebra. In: Pacific Symposium Biocomput., pp. 459–470 (2001)
Matsuoka, Y., Ghosh, S., Kitano, H.: Consistent design schematics for biological systems: standardization of representation in biological engineering. J. R Soc. Interface (June 3, 2009)
Guerriero, M.L., Heath, J.K., Priami, C.: An automated translation from a narrative language for biological modelling into process algebra. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 136–151. Springer, Heidelberg (2007)
Guerriero, M.L., Dudka, A., Underhill-Day, N., Heath, J.K., Priami, C.: Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway. BMC Syst. Biol. 3, 40 (2009)
Jain, E., Bairoch, A., Duvaud, S., Phan, I., Redaschi, N., Suzek, B.E., Martin, M.J., McGarvey, P., Gasteiger, E.: Infrastructure for the life sciences: design and implementation of the UniProt website. BMC Bioinformatics 10, 136 (2009)
Puig, O., Caspary, F., Rigaut, G., Rutz, B., Bouveret, E., Bragado-Nilsson, E., Wilm, M., Sraphin, B.: The tandem affinity purification (TAP) method: a general procedure of protein complex purification. Methods 24(3), 218–229 (2001)
Chung, A.S., Chin, Y.E.: Antibody array platform to monitor protein tyrosine phosphorylation in mammalian cells. Methods Mol. Biol. 527, 247–255 (2009)
Albeck, J.G., MacBeath, G., White, F.M., Sorger, P.K., Lauffenburger, D.A., Gaudet, S.: Collecting and organizing systematic sets of protein data. Nat. Rev. Mol. Cell Biol. 7(11), 803–812 (2006)
Jensen, L.J., Kuhn, M., Stark, M., Chaffron, S., Creevey, C., Muller, J., Doerks, T., Julien, P., Roth, A., Simonovic, M., Bork, P., von Mering, C.: STRING 8–a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 37(Database issue), D412–D416 (2009)
Regev, A., Panina, E.M., Silverman, W., Cardelli, L., Shapiro, E.: Bioambients: An abstraction for biological compartments. Theoretical Computer Science, 141–167 (2004)
Heath, J.K., Khan, I., van Bakel, S., Vigliotti, M.G.: Modelling intracellular fate of FGF receptors with BioAmbients. In: Proceedings of Int. Workshop Quantitative Aspects of Programming Languages (QAPL 2008). ENTCS, vol. 220, pp. 181–197 (2008)
Sabouri-Ghomi, M., Wu, Y., Hahn, K., Danuser, G.: Visualizing and quantifying adhesive signals. Curr. Opin. Cell Biol. 20(5), 541–550 (2008)
Calder, M., Gilmore, S., Hillston, J.: Modelling the influence of RKIP on the ERK signalling pathway using the stochastic process algebra PEPA. In: Priami, C., Ingólfsdóttir, A., Mishra, B., Riis Nielson, H. (eds.) Transactions on Computational Systems Biology VII. LNCS (LNBI), vol. 4230, pp. 1–23. Springer, Heidelberg (2006)
Lu, A., Tebar, F., Alvarez-Moya, B., Lpez-Alcal, C., Calvo, M., Enrich, C., Agell, N., Nakamura, T., Matsuda, M., Bachs, O.: A clathrin-dependent pathway leads to KRas signaling on late endosomes en route to lysosomes. J. Cell Biol. 184(6), 863–879 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Heath, J.K. (2009). The Equivalence between Biology and Computation. In: Degano, P., Gorrieri, R. (eds) Computational Methods in Systems Biology. CMSB 2009. Lecture Notes in Computer Science(), vol 5688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03845-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-03845-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03844-0
Online ISBN: 978-3-642-03845-7
eBook Packages: Computer ScienceComputer Science (R0)