M. Ashyraliyev, Y. Fomekong-nanfack, J. A. Kaandorp, and J. G. Blom, Systems biology: parameter estimation for biochemical models, FEBS Journal, vol.7, issue.4, pp.886-902, 2009.
DOI : 10.1111/j.1742-4658.2008.06844.x

G. Berthelot and G. , Reduction of Petri-nets, In Mathematical Foundations of Computer Science LNCS, 1976.
DOI : 10.1007/3-540-07854-1_175

M. Bodenstein, Eine Theorie der photochemischen Reaktionsgeschwindigkeiten, Zeitschrift f??r Physikalische Chemie, vol.85, issue.1, pp.22-3654, 1913.
DOI : 10.1515/zpch-1913-0112

L. Cardelli, Morphisms of reaction networks that couple structure to function, BMC Systems Biology, vol.8, issue.1, p.84, 2014.
DOI : 10.1007/s11047-008-9067-y

L. Cardelli and G. Zavattaro, On the Computational Power of Biochemistry, 2008.
DOI : 10.1007/978-3-540-85101-1_6

V. Danos, J. Feret, W. Fontana, R. Harmer, and J. Krivine, Abstracting the Differential Semantics of Rule-Based Models: Exact and Automated Model Reduction, 2010 25th Annual IEEE Symposium on Logic in Computer Science, pp.362-381, 2010.
DOI : 10.1109/LICS.2010.44

URL : https://hal.archives-ouvertes.fr/hal-00520112

H. Jong, Modeling and Simulation of Genetic Regulatory Systems: A Literature Review, Journal of Computational Biology, vol.9, issue.1, 2002.
DOI : 10.1089/10665270252833208

URL : https://hal.archives-ouvertes.fr/inria-00072606

F. Fages, S. Gay, and S. Soliman, Inferring Reaction Models from ODEs, Computational Methods in Systems Biology, pp.370-373, 2012.
DOI : 10.1007/978-3-642-33636-2_23

F. Fages and S. Soliman, Formal Cell Biology in Biocham, Formal Methods for Computational Systems Biology, pp.54-80, 2008.
DOI : 10.1007/978-3-540-68894-5_3

S. Gay, S. Soliman, and F. Fages, A graphical method for reducing and relating models in systems biology, Bioinformatics, vol.26, issue.18, p.26, 2010.
DOI : 10.1093/bioinformatics/btq388

URL : https://hal.archives-ouvertes.fr/hal-01431335

A. N. Gorban and I. V. Karlin, Method of invariant manifold for chemical kinetics, Chemical Engineering Science, vol.58, issue.21, pp.4751-4768, 2003.
DOI : 10.1016/j.ces.2002.12.001

A. N. Gorban, I. V. Karlin, P. Ilg, and H. C. Öttinger, Corrections and enhancements of quasi-equilibrium states, Journal of Non-Newtonian Fluid Mechanics, vol.96, issue.1-2, pp.203-219, 2001.
DOI : 10.1016/S0377-0257(00)00135-X

M. Gossen and H. Bujard, Tight control of gene expression in mammalian cells by tetracycline-responsive promoters., Proceedings of the National Academy of Sciences of the United States of America, 1992.
DOI : 10.1073/pnas.89.12.5547

M. Gossen, S. Freundlieb, G. Bender, G. Müller, W. Hillen et al., Transcriptional activation by tetracyclines in mammalian cells, Science, vol.268, issue.5218, p.268, 1995.
DOI : 10.1126/science.7792603

Z. Huang, C. Moya, A. Jayaraman, and J. Hahn, Using the Tet-On system to develop a procedure for extracting transcription factor activation dynamics, Molecular BioSystems, vol.4, issue.2, 2010.
DOI : 10.1039/c003229h

M. John, C. Lhoussaine, J. Niehren, and C. Versari, Biochemical Reaction Rules with Constraints, 20th European Symposium on Programming Languages (ESOP), pp.338-357, 2011.
DOI : 10.1007/978-3-540-71316-6_28

URL : https://hal.archives-ouvertes.fr/inria-00544387

E. L. King and C. Altman, A Schematic Method of Deriving the Rate Laws for Enzyme-Catalyzed Reactions, The Journal of Physical Chemistry, vol.60, issue.10, pp.1375-1378, 1956.
DOI : 10.1021/j150544a010

H. Kitano, Systems Biology: A Brief Overview, Science, vol.295, issue.5560, pp.1662-1664, 2002.
DOI : 10.1126/science.1069492

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.7761

F. Lemaire, A. Sedoglavic, and A. Urguplu, Moving frame based strategies for reduction of ordinary differential/recurrence systems using their expanded lie point symmetries, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00212331

G. Madelaine, C. Lhoussaine, and J. Niehren, Attractor Equivalence: An Observational Semantics for Reaction Networks, Formal Methods in Macro-Biology, pp.82-101, 2014.
DOI : 10.1007/978-3-319-10398-3_7

URL : https://hal.archives-ouvertes.fr/hal-00990924

U. Mäder, A. G. Schmeisky, L. A. Flórez, and J. Stülke, SubtiWiki--a comprehensive community resource for the model organism Bacillus subtilis, Nucleic Acids Research, vol.40, issue.D1, pp.1278-1287, 2012.
DOI : 10.1093/nar/gkr923

L. Michaelis and M. L. Menten, Die kinetik der invertinwirkung, Biochem. z, vol.49, pp.333-369352, 1913.

T. Murata and J. Koh, Reduction and expansion of live and safe marked graphs. Circuits and Systems, IEEE Transactions on, vol.27, issue.1, 1980.

A. M. Pitts, Operational Semantics and Program Equivalence, Applied Semantics, 2000.
DOI : 10.1007/3-540-45699-6_8

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.166

A. Regev and E. Shapiro, Cellular abstractions: Cells as computation, Nature, vol.419, issue.6905, pp.343-343, 2002.
DOI : 10.1038/419343a

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842595

M. Schmidt-schauss, D. Sabel, J. Niehren, and J. Schwinghammer, Observational program calculi and the correctness of translations, Theoretical Computer Science, vol.577, pp.98-124, 2015.
DOI : 10.1016/j.tcs.2015.02.027

URL : https://hal.archives-ouvertes.fr/hal-00824349

L. A. Segel and M. Slemrod, The Quasi-Steady-State Assumption: A Case Study in Perturbation, SIAM Review, vol.31, issue.3, pp.446-477, 1989.
DOI : 10.1137/1031091

S. Soliman, F. Fages, and O. Radulescu, A constraint solving approach to model reduction by tropical equilibration, WCB-ninth Workshop on Constraint Based Methods for Bioinformatics, 2013.
DOI : 10.1186/s13015-014-0024-2

URL : https://hal.archives-ouvertes.fr/hal-01098530

J. Uhlendorf, S. Bottani, F. Fages, P. Hersen, and G. Batt, TOWARDS REAL-TIME CONTROL OF GENE EXPRESSION: CONTROLLING THE HOG SIGNALING CASCADE, Pacific Symposium On Biocomputing, pp.338-349, 2011.
DOI : 10.1142/9789814335058_0035

J. Uhlendorf, A. Miermont, T. Delaveau, G. Charvin, F. Fages et al., Long-term model predictive control of gene expression at the population and single-cell levels, Proceedings of the National Academy of Sciences, p.2012
DOI : 10.1073/pnas.1206810109