Abstract
Methods for model integration have become increasingly popular for understanding of the interplay between biological processes. In this work, we introduce an approach for coupling models taking uncertainties concerning the crosstalk into account. Using constraintbased modeling and formal verification techniques, a pool of possible integrated models is generated in agreement with previously validated behavior of the isolated models as well as additional experimental observations. Correlation- and causality-based analysis allows us to uncover the importance of particular crosstalk connections for specific functionalities leading to new biological insights and starting points for experimental design. We illustrate our approach studying crosstalk between the MAPK and mTor signaling pathways.
Keywords
- Systems Biology
- Logical Modeling
- Crosstalk Analysis
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References
Baier, C., Katoen, J.-P.: Principles of Model Checking. The MIT Press (2008)
Bernot, G., Comet, J.-P., Richard, A., Guespin, J.: Application of formal methods to biological regulatory networks: extending Thomas’ asynchronous logical approach with temporal logic. Journal of Theoretical Biology 229(3), 339–347 (2004)
Courtney, K.D., Corcoran, R.B., Engelman, J.A.: The PI3K pathway as drug target in human cancer. Journal of Clinical Oncology 28(6), 1075–1083 (2010)
Gallet, E., Manceny, M., Gall, P.L., Ballarini, P.: Adapting LTL model checking for inferring biological parameters. In: AFADL 2014, p. 46 (2014)
Grieco, L., Calzone, L., Bernard-Pierrot, I., Radvanyi, F., Kahn-Perlès, B., Thieffry, D.: Integrative Modelling of the Influence of MAPK Network on Cancer Cell Fate Decision. PLoS Computational Biology 9(10), e1003286 (2013)
Guziolowski, C., Videla, S., Eduati, F., Thiele, S., Cokelaer, T., Siegel, A., Saez-Rodriguez, J.: Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming. Bioinformatics 29(18), 2320–2326 (2013)
Hu, H., Goltsov, A., Bown, J.L., Sims, A.H., Langdon, S.P., Harrison, D.J., Faratian, D.: Feedforward and feedback regulation of the MAPK and PI3K oscillatory circuit in breast cancer. Cellular Signalling 25(1), 26–32 (2013)
Kholodenko, B.N.: Negative feedback and ultrasensitivity can bring about oscillations in the mitogen-activated protein kinase cascades. European Journal of Biochemistry 267(6), 1583–1588 (2000)
Klarner, H., Streck, A., Šafránek, D., Kolčák, J., Siebert, H.: Parameter Identification and Model Ranking of Thomas Networks. In: Gilbert, D., Heiner, M. (eds.) CMSB 2012. LNCS, vol. 7605, pp. 207–226. Springer, Heidelberg (2012)
Mendes, N.D., Lang, F., Le Cornec, Y.-S., Mateescu, R., Batt, G., Chaouiya, C.: Composition and abstraction of logical regulatory modules: application to multicellular systems. Bioinformatics 29(6), 749–757 (2013)
Mendoza, M.C., Er, E.E., Blenis, J.: The Ras-ERK and PI3K-mTOR pathways: cross-talk and compensation. Trends in Biochemical Sciences 36(6), 320–328 (2011)
Samaga, R., Saez-Rodriguez, J., Alexopoulos, L.G., Sorger, P.K., Klamt, S.: The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. PLoS Computational Biology 5(8), e1000438 (2009)
Siebert, H.: Analysis of discrete bioregulatory networks using symbolic steady states. Bulletin of Mathematical Biology 73(4), 873–898 (2011)
Stelling, J., Mendes, P., Tonin, F., Klipp, E., Zecchina, R., Heinemann, M., Przulj, N., Wodke, J., Stoma, S., Kaltenbach, H.: et al. Defining modeling strategies for systems biology. In: Technical report, FutureSysBio Workshop (2011)
Streck, A., Kolcák, J., Siebert, H., Šafránek, D.: Esther: Introducing an online platform for parameter identification of boolean networks. In: Gupta, A., Henzinger, T.A. (eds.) CMSB 2013. LNCS, vol. 8130, pp. 257–258. Springer, Heidelberg (2013)
Thomas, R.: Regulatory networks seen as asynchronous automata: a logical description. Journal of Theoretical Biology 153(1), 1–23 (1991)
Wang, R.-S., Saadatpour, A., Albert, R.: Boolean modeling in systems biology: an overview of methodology and applications. Physical Biology 9(5), 055001 (2012)
Will, M., Qin, A.C.R., Toy, W., Yao, Z., Rodrik-Outmezguine, V., Schneider, C., Huang, X., Monian, P., Jiang, X., De Stanchina, E., et al.: Rapid induction of apoptosis by PI3K inhibitors is dependent upon their transient inhibition of RAS-ERK signaling. Cancer discovery CD-13 (2014)
Winter, J.N., Jefferson, L.S., Kimball, S.R.: ERK and Akt signaling pathways function through parallel mechanisms to promote mTORC1 signaling. American Journal of Physiology - Cell Physiology 300(5), C1172–C1180 (2011)
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Thobe, K., Streck, A., Klarner, H., Siebert, H. (2014). Model Integration and Crosstalk Analysis of Logical Regulatory Networks. In: Mendes, P., Dada, J.O., Smallbone, K. (eds) Computational Methods in Systems Biology. CMSB 2014. Lecture Notes in Computer Science(), vol 8859. Springer, Cham. https://doi.org/10.1007/978-3-319-12982-2_3
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DOI: https://doi.org/10.1007/978-3-319-12982-2_3
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