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A Foundational Framework for Step-by-step Model Construction

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Języki publikacji
EN
Abstrakty
EN
Constructing large biomodels de-novo is a computationally expensive process, requiring large sets of high-quality data. An alternative approach is to construct them from smaller existing models through various operations such as union, intersection, difference, and refinement. We introduce in this paper a foundational framework for biomodel construction capturing these operations, and we discuss some of their properties.
Wydawca
Rocznik
Strony
15--24
Opis fizyczny
Bibliogr. 22 poz.
Twórcy
autor
  • Computational Biomodeling Laboratory, Åbo Akademi University and Turku Centre for Computer Science, Turku, Finland
autor
  • Computational Biomodeling Laboratory, Åbo Akademi University and Turku Centre for Computer Science, Turku, Finland
Bibliografia
  • [1] Buckingham SD. To build a better model. Nat Meth, 2007;4(4):367–374. URL http://dx.doi.org/10.1038/nmeth0407-367.
  • [2] Back R, von Wright J. Refinement Calculus - A Systematic Introduction. Graduate Texts in Computer Science. Springer, 1998. ISBN:978-0-387-98417-9. doi:10.1007/978-1-4612-1674-2. URL http://dx.doi.org/10.1007/978-1-4612-1674-2.
  • [3] Murphy E, Danos V, Feret J, Krivine J, Harmer R. Elements of Computational Systems Biology, chapter Rule Based Modelling and Model Refinement, pp. 83–114. Wiley Book Series on Bioinformatics. John Wiley & Sons, Inc., 2010.
  • [4] Iancu B, Czeizler E, Czeizler E, Petre I. Quantitative Refinement of Reaction Models. International Journal of Unconventional Computing, 2012;8(5-6):529–550.
  • [5] Gratie DE, Iancu B, Azimi S, Petre I. Quantitative Model Refinement in Four Different Frameworks, with Applications to the Heat Shock Response. In: Petre L, Sekerinski E (eds.), From Action Systems to Distributed Systems, pp. 201–2014. Taylor & Francis, 2016.
  • [6] Azimi S, Czeizler E, Gratie C, Gratie D, Iancu B, Ibssa N, Petre I, Rogojin V, Shadbahr T, Shokri F. An Excursion Through Quantitative Model Refinement. In: Rozenberg et al. [17], 2015 pp. 25–47. doi: 10.1007/978-3-319-28475-0_3. URL http://dx.doi.org/10.1007/978-3-319-28475-0_3.
  • [7] Karr JR, Sanghvi JC, Macklin DN, Gutschow MV, Jacobs JM, Bolival B, Assad-Garcia N, Glass JI, Covert MW. A whole-cell computational model predicts phenotype from genotype. Cell, 2012. 150(2):389–401.
  • [8] Gratie C, Petre I. Complete characterization for the fit-preserving data refinement of mass-action reaction networks. Theoretical Computer Science, 2016;641:11–24. doi:10.1016/j.tcs.2016.03.027. URL http://dx.doi.org/10.1016/j.tcs.2016.03.027.
  • [9] Gratie DE, Gratie C. Composition Colored Petri Nets for the Refinement of Reaction-based Models. Electronic Notes in Theoretical Computer Science, 2016;326:51–72.
  • [10] Gratie D, Iancu B, Petre I. ODE Analysis of Biological Systems. In: Bernardo et al. [20], 2013 pp. 29–62. doi:10.1007/978-3-642-38874-3_2. URL http://dx.doi.org/10.1007/978-3-642-38874-3_2.
  • [11] Suzuki I, Murata T. A Method for Stepwise Refinement and Abstraction of Petri Nets. J. Comput. Syst. Sci., 1983;27(1):51–76. doi:10.1016/0022-0000(83)90029-6. URL http://dx.doi.org/10.1016/0022-0000(83)90029-6.
  • [12] Pistore M, Sangiorgi D. A Partition Refinement Algorithm for the π-Calculus. Information and Computation, 2001;164(2):264–321. doi:10.1006/inco.2000.2895. URL http://dx.doi.org/10.1006/inco.2000.2895.
  • [13] Păun G, Rozenberg G. A guide to membrane computing. Theor. Comput. Sci., 2002;287(1):73–100. doi: 10.1016/S0304-3975(02)00136-6. URL http://dx.doi.org/10.1016/S0304-3975(02)00136-6.
  • [14] Pérez-Jiménez MJ, Romero-Campero FJ. A Study of the Robustness of the EGFR Signalling Cascade Using Continuous Membrane Systems. In: Mira and Álvarez [22], 2005 pp. 268–278. doi: 10.1007/11499220_28. URL http://dx.doi.org/10.1007/11499220_28.
  • [15] Bartocci E, Lió P. Computational Modeling, Formal Analysis, and Tools for Systems Biology. PLOS Computational Biology, 2016;12(1):1–22. doi:10.1371/journal.pcbi.1004591. URL https://doi.org/10.1371/journal.pcbi.1004591.
  • [16] Gratie C, Petre I. Fit-Preserving Data Refinement of Mass-Action Reaction Networks. In: Beckmann et al. [19], 2014 pp. 204–213. doi:10.1007/978-3-319-08019-2_21. URL http://dx.doi.org/10.1007/978-3-319-08019-2_21.
  • [17] Rozenberg G, Salomaa A, Sempere JM, Zandron C (eds.). Membrane Computing - 16th International Conference, CMC 2015, Valencia, Spain, August 17-21, 2015, Revised Selected Papers, volume 9504 of Lecture Notes in Computer Science. Springer, 2015. ISBN 978-3-319-28474-3. doi:10.1007/978-3-319-28475-0. URL http://dx.doi.org/10.1007/978-3-319-28475-0.
  • [18] Czeizler E, Czeizler E, Iancu B, Petre I. Quantitative Model Refinement as a Solution to the Combinatorial Size Explosion of Biomodels. Electr. Notes Theor. Comput. Sci., 2012;284:35–53. doi: 10.1016/j.entcs.2012.05.014. URL http://dx.doi.org/10.1016/j.entcs.2012.05.014.
  • [19] Beckmann A, Csuhaj-Varjú E, Meer K (eds.). Language, Life, Limits - 10th Conference on Computability in Europe, CiE 2014, Budapest, Hungary, June 23-27, 2014. Proceedings, volume 8493 of Lecture Notes in Computer Science. Springer, 2014. ISBN 978-3-319-08018-5. doi:10.1007/978-3-319-08019-2. URL http://dx.doi.org/10.1007/978-3-319-08019-2.
  • [20] Bernardo M, de Vink EP, Pierro AD, Wiklicky H (eds.). Formal Methods for Dynamical Systems - 13th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2013, Bertinoro, Italy, June 17-22, 2013. Advanced Lectures, volume 7938 of Lecture Notes in Computer Science. Springer, 2013. ISBN 978-3-642-38873-6. doi:10.1007/978-3-642-38874-3. URL http://dx.doi.org/10.1007/978-3-642-38874-3.
  • [21] Volterra V. doi:10.1093/icesjms/3.1.3.
  • [22] Mira J, Álvarez JR (eds.). Mechanisms, Symbols, and Models Underlying Cognition: First International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I, volume 3561 of Lecture Notes in Computer Science. Springer, 2005. ISBN 3-540-26298-9.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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