I. Akyildiz, F. Brunetti, and C. Blázquez, Nanonetworks: A new communication paradigm, Computer Networks, vol.52, issue.12, pp.2260-2279, 2008.
DOI : 10.1016/j.comnet.2008.04.001

T. Nakano, A. Eckford, and T. Haraguchi, Molecular Communication, 2013.
DOI : 10.1017/CBO9781139149693

F. Farsad, H. Yilmaz, A. Eckford, C. Chae, and W. Guo, A Comprehensive Survey of Recent Advancements in Molecular Communication, IEEE Communications Surveys & Tutorials, vol.18, issue.3, pp.1887-1919, 2016.
DOI : 10.1109/COMST.2016.2527741

M. Miller and B. Bassler, Quorum Sensing in Bacteria, Annual Review of Microbiology, vol.55, issue.1, pp.165-199, 2001.
DOI : 10.1146/annurev.micro.55.1.165

P. Melke, P. Sahlin, A. Levchenko, and H. Jönsson, A Cell-Based Model for Quorum Sensing in Heterogeneous Bacterial Colonies, PLoS Computational Biology, vol.3, issue.6, 2010.
DOI : 10.1371/journal.pcbi.1000819.s015

M. Pierobon and F. Akyildiz, Capacity of a Diffusion-Based Molecular Communication System With Channel Memory and Molecular Noise, IEEE Transactions on Information Theory, vol.59, issue.2, pp.942-954, 2013.
DOI : 10.1109/TIT.2012.2219496

K. Srinivas, A. Eckford, and R. Adve, Molecular Communication in Fluid Media: The Additive Inverse Gaussian Noise Channel, IEEE Transactions on Information Theory, vol.58, issue.7, pp.4678-4692, 2012.
DOI : 10.1109/TIT.2012.2193554

T. Nakano, Y. Okaie, and J. Liu, Channel Model and Capacity Analysis of Molecular Communication with Brownian Motion, IEEE Communications Letters, vol.16, issue.6, pp.797-800, 2012.
DOI : 10.1109/LCOMM.2012.042312.120359

H. Li, S. Moser, and D. Guo, Capacity of the Memoryless Additive Inverse Gaussian Noise Channel, IEEE Journal on Selected Areas in Communications, vol.32, issue.12, pp.2315-2329, 2014.
DOI : 10.1109/JSAC.2014.2367673

M. Egan, Y. Deng, M. Elkashlan, and T. Duong, Variance-constrained capacity of the molecular timing channel with synchronization error, 2014 IEEE Global Communications Conference, 2014.
DOI : 10.1109/GLOCOM.2014.7037016

B. Li, M. Sun, S. Wang, W. Guo, and C. Zhao, Local Convexity Inspired Low-Complexity Noncoherent Signal Detector for Nanoscale Molecular Communications, IEEE Transactions on Communications, vol.64, issue.5, pp.2079-2091, 2016.
DOI : 10.1109/TCOMM.2016.2543734

URL : http://wrap.warwick.ac.uk/77513/1/WRAP_Weisi_Local_convexity_TCOM_R4.pdf

T. Mai, M. Egan, T. Duong, and M. D. Renzo, Event Detection in Molecular Communication Networks With Anomalous Diffusion, IEEE Communications Letters, vol.21, issue.6, pp.1249-1252, 2017.
DOI : 10.1109/LCOMM.2017.2669315

URL : https://hal.archives-ouvertes.fr/hal-01671181

A. Noel, K. Cheung, and R. Schober, Improving Receiver Performance of Diffusive Molecular Communication With Enzymes, IEEE Transactions on NanoBioscience, vol.13, issue.1, pp.31-43, 2014.
DOI : 10.1109/TNB.2013.2295546

B. Atakan, O. Akan, and S. Balasubramiam, Body area nanonetworks with molecular communications in nanomedicine, IEEE Communications Magazine, vol.50, issue.1, 2012.
DOI : 10.1109/MCOM.2012.6122529

S. Haykin, Cognitive radio: brain-empowered wireless communications, IEEE Journal on Selected Areas in Communications, vol.23, issue.2, pp.201-220, 2005.
DOI : 10.1109/JSAC.2004.839380

URL : http://www.eecs.berkeley.edu/~dtse/3r_haykin_jsac05.pdf

Y. Chahibi and I. Akyildiz, Molecular Communication Noise and Capacity Analysis for Particulate Drug Delivery Systems, IEEE Transactions on Communications, vol.62, issue.11, pp.3891-3903, 2014.
DOI : 10.1109/TCOMM.2014.2360678

M. Feinberg, Chemical reaction network structure and the stability of complex isothermal reactors???I. The deficiency zero and deficiency one theorems, Chemical Engineering Science, vol.42, issue.10, pp.2229-2268, 1987.
DOI : 10.1016/0009-2509(87)80099-4

S. Reed, Essential Physiological Biochemistry, 2009.

V. Chellaboina, S. Bhat, W. Haddad, and D. Bernstein, Modeling and analysis of mass-action kinetics, IEEE Control Systems Magazine, vol.29, issue.4, 2009.
DOI : 10.1109/MCS.2009.932926

G. Craciun and M. Feinberg, Multiple Equilibria in Complex Chemical Reaction Networks: I. The Injectivity Property, SIAM Journal on Applied Mathematics, vol.65, issue.5, pp.1526-1546, 2005.
DOI : 10.1137/S0036139904440278

URL : http://www.math.wisc.edu/~craciun/PAPERS/SIAM_Craciun_Feinberg_2.pdf

H. Fogler, Elements of Chemical Reaction Engineering, 2006.

D. Angeli, P. Leenheer, and E. Sontag, A Petri net approach to the study of persistence in chemical reaction networks, Mathematical Biosciences, vol.210, issue.2, 2006.
DOI : 10.1016/j.mbs.2007.07.003

A. Babtie, N. Tokuriki, and F. Hollfelder, What makes an enzyme promiscuous?, Current Opinion in Chemical Biology, vol.14, issue.2, pp.200-207, 2010.
DOI : 10.1016/j.cbpa.2009.11.028

S. Schnell and C. Mendoza, Closed Form Solution for Time-dependent Enzyme Kinetics, Journal of Theoretical Biology, vol.187, issue.2, pp.207-212, 1997.
DOI : 10.1006/jtbi.1997.0425

M. Gopalkrishnan, A Scheme for Molecular Computation of Maximum Likelihood Estimators for Log-Linear Models
DOI : 10.1021/sb400169s

G. Craciun, F. Nazarov, and C. Pantea, Persistence and Permanence of Mass-Action and Power-Law Dynamical Systems, SIAM Journal on Applied Mathematics, vol.73, issue.1, pp.305-329, 2013.
DOI : 10.1137/100812355

I. Otero-muras, P. Yordanov, and J. Stelling, Chemical Reaction Network Theory elucidates sources of multistability in interferon signaling, PLOS Computational Biology, vol.10, issue.87, 2017.
DOI : 10.1371/journal.pcbi.1005454.s002

A. Van-der-schaft, S. Rao, and B. Jayawardhana, A network dynamics approach to chemical reaction networks, International Journal of Control, vol.49, issue.4, 2016.
DOI : 10.1371/journal.pcbi.1003186

H. Yilmaz, Y. Cho, W. Guo, and C. Chae, Interference reduction via enzyme deployment for molecular communication, Electronics Letters, vol.52, issue.13, pp.1094-1096, 2016.
DOI : 10.1049/el.2016.0411

URL : http://wrap.warwick.ac.uk/78610/1/yilmaz2015enzymeDeployment.pdf

A. Noel, K. Cheung, R. Schober, D. Makrakis, and A. Hafid, Simulating with AcCoRD: Actor-based Communication via Reaction???Diffusion, Nano Communication Networks, pp.44-75, 2017.
DOI : 10.1016/j.nancom.2017.02.002

URL : http://arxiv.org/pdf/1612.00485

K. Fellner, W. Prager, and B. Tang, The entropy method for reaction-diffusion systems without detailed balance: First order chemical reaction networks, Kinetic and Related Models, vol.10, issue.4, pp.1055-1087, 2017.
DOI : 10.3934/krm.2017042

F. Horn and R. Jackson, General mass action kinetics, Archive for Rational Mechanics and Analysis, vol.47, issue.2, pp.81-116, 1972.
DOI : 10.1007/BF00251225