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For: Clairambault J. Modelling Physiological and Pharmacological Control on Cell Proliferation to Optimise Cancer Treatments. Math Model Nat Phenom 2009;4:12-67. [DOI: 10.1051/mmnp/20094302] [Cited by in Crossref: 25] [Cited by in F6Publishing: 14] [Article Influence: 1.9] [Reference Citation Analysis]
Number Citing Articles
1 Benosman C, Aïnseba B, Ducrot A. Optimization of Cytostatic Leukemia Therapy in an Advection–Reaction–Diffusion Model. J Optim Theory Appl 2015;167:296-325. [DOI: 10.1007/s10957-014-0667-7] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
2 Pujo-menjouet L, Volpert V. Blood Cell Dynamics: Half of a Century of Modelling. Math Model Nat Phenom 2016;11:92-115. [DOI: 10.1051/mmnp/201611106] [Cited by in Crossref: 29] [Cited by in F6Publishing: 10] [Article Influence: 4.8] [Reference Citation Analysis]
3 Steimer JL, Dahl SG, De Alwis DP, Gundert-Remy U, Karlsson MO, Martinkova J, Aarons L, Ahr HJ, Clairambault J, Freyer G, Friberg LE, Kern SE, Kopp-Schneider A, Ludwig WD, De Nicolao G, Rocchetti M, Troconiz IF. Modelling the genesis and treatment of cancer: the potential role of physiologically based pharmacodynamics. Eur J Cancer 2010;46:21-32. [PMID: 19954965 DOI: 10.1016/j.ejca.2009.10.011] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 0.7] [Reference Citation Analysis]
4 Billy F, Clairambault J; INRIA Paris-Rocquencourt, Domaine de Voluceau, Rocquencourt, B.P. 105, F-78153 Le Chesnay Cedex. . Discrete & Continuous Dynamical Systems - B 2013;18:865-89. [DOI: 10.3934/dcdsb.2013.18.865] [Cited by in Crossref: 15] [Cited by in F6Publishing: 6] [Article Influence: 1.7] [Reference Citation Analysis]
5 Chisholm RH, Lorenzi T, Clairambault J. Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation. Biochim Biophys Acta 2016;1860:2627-45. [PMID: 27339473 DOI: 10.1016/j.bbagen.2016.06.009] [Cited by in Crossref: 46] [Cited by in F6Publishing: 34] [Article Influence: 7.7] [Reference Citation Analysis]
6 Ledzewicz U, Schättler H. Application of mathematical models to metronomic chemotherapy: What can be inferred from minimal parameterized models? Cancer Lett 2017;401:74-80. [PMID: 28323033 DOI: 10.1016/j.canlet.2017.03.021] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 1.8] [Reference Citation Analysis]
7 Engelhart M, Lebiedz D, Sager S. Optimal control for selected cancer chemotherapy ODE models: A view on the potential of optimal schedules and choice of objective function. Mathematical Biosciences 2011;229:123-34. [DOI: 10.1016/j.mbs.2010.11.007] [Cited by in Crossref: 59] [Cited by in F6Publishing: 35] [Article Influence: 5.4] [Reference Citation Analysis]
8 Billy F, Clairambault J, Fercoq O. Optimisation of Cancer Drug Treatments Using Cell Population Dynamics. In: Ledzewicz U, Schättler H, Friedman A, Kashdan E, editors. Mathematical Methods and Models in Biomedicine. New York: Springer; 2013. pp. 265-309. [DOI: 10.1007/978-1-4614-4178-6_10] [Cited by in Crossref: 13] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
9 McQueen A, Escuer J, Aggarwal A, Kennedy S, McCormick C, Oldroyd K, McGinty S. Do we really understand how drug eluted from stents modulates arterial healing? Int J Pharm 2021;601:120575. [PMID: 33845150 DOI: 10.1016/j.ijpharm.2021.120575] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 Ilieş I, Sipahi R, Zupanc GKH. Growth of adult spinal cord in knifefish: Development and parametrization of a distributed model. J Theor Biol 2018;437:101-14. [PMID: 29031516 DOI: 10.1016/j.jtbi.2017.10.012] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 1.2] [Reference Citation Analysis]
11 Clairambault J. Optimizing cancer pharmacotherapeutics using mathematical modeling and a systems biology approach. Per Med 2011;8:271-86. [PMID: 29783516 DOI: 10.2217/pme.11.20] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 0.7] [Reference Citation Analysis]
12 A. Fernández L, Pola C; Dep. Matemáticas, Estadística y Computación, Universidad de Cantabria, Avda. de los Castros, s/n, 39005 Santander. . Discrete & Continuous Dynamical Systems - B 2014;19:1563-88. [DOI: 10.3934/dcdsb.2014.19.1563] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
13 Billy F, Clairambaultt J, Fercoq O, Gaubertt S, Lepoutre T, Ouillon T, Saito S. Synchronisation and control of proliferation in cycling cell population models with age structure. Mathematics and Computers in Simulation 2014;96:66-94. [DOI: 10.1016/j.matcom.2012.03.005] [Cited by in Crossref: 23] [Cited by in F6Publishing: 8] [Article Influence: 2.9] [Reference Citation Analysis]
14 Clairambault J, Fercoq O, Bocharov G, Clairambault J, Volpert V. Physiologically Structured Cell Population Dynamic Models with Applications to Combined Drug Delivery Optimisation in Oncology. Math Model Nat Phenom 2016;11:45-70. [DOI: 10.1051/mmnp/201611604] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.4] [Reference Citation Analysis]
15 Eliaš J, Dimitrio L, Clairambault J, Natalini R. The p53 protein and its molecular network: modelling a missing link between DNA damage and cell fate. Biochim Biophys Acta 2014;1844:232-47. [PMID: 24113167 DOI: 10.1016/j.bbapap.2013.09.019] [Cited by in Crossref: 46] [Cited by in F6Publishing: 42] [Article Influence: 5.1] [Reference Citation Analysis]
16 Eliaš J, Dimitrio L, Clairambault J, Natalini R. The dynamics of p53 in single cells: physiologically based ODE and reaction-diffusion PDE models. Phys Biol 2014;11:045001. [PMID: 25075792 DOI: 10.1088/1478-3975/11/4/045001] [Cited by in Crossref: 26] [Cited by in F6Publishing: 18] [Article Influence: 3.3] [Reference Citation Analysis]