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Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1H. Martin.

    Data analysis and integro-differential models in cellular biology, Sorbonne Université - Laboratoire Jacques-Louis Lions, July 2019.

  • 2M. Mezache.

    Oscillatory processes during the aggregation and the fragmentation of the amyloid fibrils, Sorbonne Université - Laboratoire Jacques-Louis Lions ; Inria Paris, December 2019.

  • 3P. Van Liedekerke.

    Quantitative modeling of cell and tissue mechanics with agent-based models, Inria Paris, Sobonne Université, March 2019, Habilitation à diriger des recherches.


Articles in International Peer-Reviewed Journals

  • 4J. Allard, M. Doumic, A. Mogilner, D. Oelz.

    Bidirectional sliding of two parallel microtubules generated by multiple identical motors, in: Journal of Mathematical Biology, April 2019. [ DOI : 10.1007/s00285-019-01369-w ]

  • 5L. Almeida, P. Bagnerini, G. Fabrini, B. D. Hughes, T. Lorenzi.

    Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model, in: ESAIM: Mathematical Modelling and Numerical Analysis, July 2019, vol. 53, no 4, pp. 1157-1190. [ DOI : 10.1051/m2an/2019010 ]

  • 6L. Almeida, F. Bubba, B. Perthame, C. Pouchol.

    Energy and implicit discretization of the Fokker-Planck and Keller-Segel type equations, in: Networks and Heterogeneous Media, March 2019, vol. 14, no 1, https://arxiv.org/abs/1803.10629. [ DOI : 10.3934/nhm.2019002 ]

  • 7L. Almeida, M. Duprez, Y. Privat, N. Vauchelet.

    Mosquito population control strategies for fighting against arboviruses, in: Mathematical Biosciences and Engineering, 2019, vol. 16, no 6, pp. 6274-6297, https://arxiv.org/abs/1901.05688. [ DOI : 10.3934/mbe.2019313 ]

  • 8L. Almeida, Y. Privat, M. Strugarek, N. Vauchelet.

    Optimal releases for population replacement strategies, application to Wolbachia, in: SIAM Journal on Mathematical Analysis, 2019, vol. 51, no 4, pp. 3170–3194, https://arxiv.org/abs/1909.02727. [ DOI : 10.1137/18M1189841 ]

  • 9E. Bernard, M. Doumic, P. Gabriel.

    Cyclic asymptotic behaviour of a population reproducing by fission into two equal parts, in: Kinetic and Related Models , June 2019, vol. 12, no 3, pp. 551-571, https://arxiv.org/abs/1609.03846. [ DOI : 10.3934/krm.2019022 ]

  • 10P.-A. Bliman, D. Cardona-Salgado, Y. Dumont, O. Vasilieva.

    Implementation of Control Strategies for Sterile Insect Techniques, in: Mathematical Biosciences, 2019, vol. 314, pp. 43-60. [ DOI : 10.1016/j.mbs.2019.06.002 ]

  • 11V. Boeuf, P. Robert.

    A Stochastic Analysis of a Network with Two Levels of Service, in: Queueing Systems, August 2019, vol. 92, no 3-4, 30 p, https://arxiv.org/abs/1708.09590, forthcoming. [ DOI : 10.1007/s11134-019-09617-y ]

  • 12F. Bubba, C. Pouchol, N. Ferrand, G. Vidal, L. Almeida, B. Perthame, M. Sabbah.

    A chemotaxis-based explanation of spheroid formation in 3D cultures of breast cancer cells, in: Journal of Theoretical Biology, 2019, vol. 479, pp. 73-80, https://arxiv.org/abs/1810.13162. [ DOI : 10.1016/j.jtbi.2019.07.002 ]

  • 13J. Clairambault.

    An evolutionary perspective on cancer, with applications to anticancer drug resistance modelling and perspectives in therapeutic control, in: Journal of Mathematical Study, 2019, pp. 1 - 21, forthcoming.

  • 14J. Clairambault, C. Pouchol.

    A survey of adaptive cell population dynamics models of emergence of drug resistance in cancer, and open questions about evolution and cancer, in: BIOMATH, May 2019, vol. 8, no 1, 23 p, Copyright : 2019 Clairambault et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. [ DOI : 10.11145/j.biomath.2019.05.147 ]

  • 15R. Dessalles, V. Fromion, P. Robert.

    Models of protein production with cell cycle, in: PLoS ONE, January 2020, vol. 15, no 1, 25 p, https://arxiv.org/abs/1711.06378. [ DOI : 10.1371/journal.pone.0226016 ]

  • 16P. Gabriel, H. Martin.

    Steady distribution of the incremental model for bacteria proliferation, in: Networks and Heterogeneous Media, March 2019, vol. 14, no 1, pp. 149-171, https://arxiv.org/abs/1803.04950. [ DOI : 10.3934/nhm.2019008 ]

  • 17A. Ghallab, M. Myllys, C. H. Holland, A. Zaza, W. Murad, R. Hassan, Y. A. Ahmed, T. Abbas, E. A. Abdelrahim, K. M. Schneider, M. Matz-Soja, J. Reinders, R. Gebhardt, M.-L. Berres, M. Hatting, D. Drasdo, J. Saez-Rodriguez, C. Trautwein, J. G. Hengstler.

    Influence of Liver Fibrosis on Lobular Zonation, in: Cells, December 2019, vol. 8, no 12, 1556 p. [ DOI : 10.3390/cells8121556 ]

  • 18T. Heck, D. A. Vargas, B. Smeets, H. Ramon, P. Van Liedekerke, H. Van Oosterwyck.

    The role of actin protrusion dynamics in cell migration through a degradable viscoelastic extracellular matrix: Insights from a computational model, in: PLoS Computational Biology, 2020, vol. 16, e1007250. [ DOI : 10.1371/journal.pcbi.1007250 ]

  • 19A. Igel-Egalon, F. Laferrière, M. Moudjou, J. Bohl, M. Mezache, T. Knäpple, L. Herzog, F. Reine, C. Jas-Duval, M. Doumic, H. Rezaei, V. Beringue.

    Early stage prion assembly involves two subpopulations with different quaternary structures and a secondary templating pathway, in: Communications Biology, December 2019, vol. 2, no 1. [ DOI : 10.1038/s42003-019-0608-y ]

  • 20G. Jankowiak, D. Peurichard, A. Reversat, C. Schmeiser, M. Sixt.

    Modelling adhesion-independent cell migration, in: Mathematical Models and Methods in Applied Sciences, 2020, forthcoming. [ DOI : 10.1142/S021820252050013X ]

  • 21F. Joly, G. Soulez, S. Lessard, C. Kauffmann, I. Vignon-Clementel.

    A cohort longitudinal study identifies morphology and hemodynamics predictors of abdominal aortic aneurysm growth, in: Annals of Biomedical Engineering, October 2019, forthcoming. [ DOI : 10.1007/s10439-019-02375-1 ]

  • 22P. V. Liedekerke, J. Neitsch, T. Johann, E. Warmt, I. Gonzàlez-Valverde, S. Hoehme, S. Grosser, J. Kaes, D. Drasdo.

    A quantitative high-resolution computational mechanics cell model for growing and regenerating tissues, in: Biomechanics and Modeling in Mechanobiology, November 2019. [ DOI : 10.1007/s10237-019-01204-7 ]

  • 23D. Martirosyan, P. Robert.

    The Equilibrium States of Large Networks of Erlang Queues, in: Advances in Applied Probability, 2020, https://arxiv.org/abs/1811.04763, forthcoming.

  • 24T. N. Nguyen, J. Clairambault, T. Jaffredo, B. Perthame, D. Salort.

    Adaptive dynamics of hematopoietic stem cells and their supporting stroma: A model and mathematical analysis, in: Mathematical Biosciences and Engineering, May 2019, vol. 16, no 05, pp. 4818–4845. [ DOI : 10.3934/mbe.2019243 ]

  • 25B. Perthame, N. Vauchelet, Z. Wang.

    The Flux Limited Keller-Segel System; Properties and Derivation from Kinetic Equations, in: Revista Matemática Iberoamericana, 2019, https://arxiv.org/abs/1801.07062, forthcoming.

  • 26D. Peurichard, M. Ousset, J. Paupert, B. Aymard, A. Lorsignol, L. Casteilla, P. Degond.

    Extra-cellular matrix rigidity may dictate the fate of injury outcome, in: Journal of Theoretical Biology, May 2019, vol. 469, pp. 127-136. [ DOI : 10.1016/j.jtbi.2019.02.017 ]

  • 27B. Piccoli, N. Pouradier Duteil, E. Trélat.

    Sparse control of Hegselmann-Krause models: Black hole and declustering, in: SIAM Journal on Control and Optimization, 2019, vol. 57, no 4, pp. 2628–2659. [ DOI : 10.1137/18M1168911 ]

  • 28C. Pouchol, E. Trélat, E. Zuazua.

    Phase portrait control for 1D monostable and bistable reaction-diffusion equations, in: Nonlinearity, 2019, vol. 32, no 3, pp. 884–909, https://arxiv.org/abs/1805.10786. [ DOI : 10.1088/1361-6544/aaf07e ]

  • 29M. Rabé, S. Dumont, A. Álvarez-Arenas, H. Janati, J. Belmonte-Beitia, G. F. Calvo, C. Thibault-Carpentier, Q. Séry, C. Chauvin, N. Joalland, F. Briand, S. Blandin, E. Scotet, C. Pecqueur, J. Clairambault, L. Oliver, V. Pérez-García, A. M. Nadaradjane, P.-F. Cartron, C. Gratas, F. Vallette.

    Identification of a transient state during the acquisition of temozolomide resistance in glioblastoma, in: Cell Death and Disease, January 2020, vol. 11, no 1. [ DOI : 10.1038/s41419-019-2200-2 ]

  • 30P. Robert.

    Mathematical Models of Gene Expression, in: Probability Surveys, October 2019, vol. 16, 56 p, https://arxiv.org/abs/1905.02578.

  • 31P. Robert, W. Sun.

    On the Asymptotic Distribution of Nucleation Times of Polymerization Processes, in: SIAM Journal on Applied Mathematics, October 2019, vol. 79, no 5, 27 p, https://arxiv.org/abs/1712.08347. [ DOI : 10.1137/19M1237508 ]

  • 32P. Robert, A. Véber.

    A Scaling Analysis of a Star Network with Logarithmic Weights, in: Stochastic Processes and their Applications, 2019, https://arxiv.org/abs/1609.04180 . [ DOI : 10.1016/j.spa.2018.06.002 ]

  • 33M. Strugarek, L. Dufour, N. Vauchelet, L. Almeida, B. Perthame, D. A. M. Villela.

    Oscillatory regimes in a mosquito population model with larval feedback on egg hatching, in: Journal of Biological Dynamics, 2019, vol. 13, no 1, pp. 269-300, https://arxiv.org/abs/1801.03701. [ DOI : 10.1080/17513758.2019.1593524 ]

  • 34W. Sun, P. Robert.

    Analysis of Large Urn Models with Local Mean-Field Interactions, in: Electronic Journal of Probability, April 2019, vol. 24, no 45, 33 p, https://arxiv.org/abs/1802.05064, forthcoming.

  • 35J. Torrent, D. Martin, S. Noinville, Y. Yin, M. Doumic, M. Moudjou, V. V. Beringue, H. Rezaei.

    Pressure Reveals Unique Conformational Features in Prion Protein Fibril Diversity, in: Scientific Reports, 2019, vol. 9, 2802 p. [ DOI : 10.1038/s41598-019-39261-8 ]

  • 36B. Ujvari, C. Jacqueline, D. Missé, V. Amar, J. Fitzpatrick, G. Jennings, C. Beckmann, S. Rome, P. Biro, R. Gatenby, J. Brown, F. Thomas, L. Almeida.

    Obesity paradox in cancer: Is bigger really better?, in: Evolutionary Applications, April 2019, vol. 12, no 6, pp. 1092-1095. [ DOI : 10.1111/eva.12790 ]

  • 37P. Van Liedekerke, J. Neitsch, T. Johann, K. Alessandri, P. Nassoy, D. Drasdo.

    Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines, in: PLoS Computational Biology, March 2019, vol. 15, no 3, e1006273. [ DOI : 10.1371/journal.pcbi.1006273 ]

  • 38P. Van Liedekerke, J. Neitsch, T. Johann, K. Alessandri, P. Nassoy, D. Drasdo.

    Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines, in: PLoS Computational Biology, March 2019, vol. 15, no 3, e1006273. [ DOI : 10.1371/journal.pcbi.1006273 ]


International Conferences with Proceedings

  • 39P.-A. Bliman.

    Feedback Control Principles for Biological Control of Dengue Vectors, in: European Control Conference ECC19, Naples, Italy, June 2019, 6 p, The last version of this manuscript has been accepted for publication in the Proceedings of European Control Conference ECC19. A complete version of the report appeared in arXiv, and is available at: http://arxiv.org/abs/1903.00730.

  • 40R. Ushirobira, D. Efimov, P.-A. Bliman.

    Estimating the infection rate of a SIR epidemic model via differential elimination, in: ECC 2019 - 18th European Control Conference, Naples, Italy, June 2019.


Other Publications

References in notes
  • 60L. Almeida, R. H. Chisholm, J. Clairambault, T. Lorenzi, A. Lorz, C. Pouchol, E. Trélat.

    Why Is Evolution Important in Cancer and What Mathematics Should Be Used to Treat Cancer? Focus on Drug Resistance, in: Trends in Biomathematics: Modeling, Optimization and Computational Problems: Selected works from the BIOMAT Consortium Lectures, Moscow 2017, Springer International Publishing, August 2018, pp. 107-120.

  • 61L. Alphey.

    Genetic control of mosquitoes, in: Annual review of entomology, 2014, vol. 59.
  • 62A. Armiento.

    Inverse problems and data assimilation methods applied to protein polymerisation, Université Paris 7 - Diderot, January 2017.

  • 63A. Armiento, M. Doumic, P. Moireau, H. Rezaei.

    Estimation from Moments Measurements for Amyloid Depolymerisation, in: Journal of Theoretical Biology, March 2016. [ DOI : 10.1016/j.jtbi.2016.02.037 ]

  • 64A. Armiento, P. Moireau, D. Martin, N. Lepejova, M. Doumic, H. Rezaei.

    The mechanism of monomer transfer between two structurally distinct PrP oligomers, in: PLoS ONE, July 2017, vol. 12, no 7. [ DOI : 10.1371/journal.pone.0180538 ]

  • 65J. L. Avila Alonso, C. Bonnet, J. Clairambault, H. Ozbay, S.-I. Niculescu, F. Merhi, A. Ballesta, R. Tang, J.-P. Marie.

    Analysis of a New Model of Cell Population Dynamics in Acute Myeloid Leukemia, in: Delay Systems : From Theory to Numerics and Applications, T. Vyhlídal, J.-F. Lafay, R. Sipahi (editors), Advances in Delays and Dynamics, Springer, January 2014, vol. 1, pp. 315-328. [ DOI : 10.1007/978-3-319-01695-5_23 ]

  • 66J. L. Avila Alonso, C. Bonnet, E. Fridman, F. Mazenc, J. Clairambault.

    Stability analysis of PDE's modelling cell dynamics in Acute Myeloid Leukemia, in: 53rd IEEE Conference on Decision and Control, Los Angeles, United States, December 2014.

  • 67J. L. Avila Alonso, C. Bonnet, H. Ozbay, J. Clairambault, S.-I. Niculescu.

    A coupled model for healthy and cancer cells dynamics in Acute Myeloid Leukemia, in: The 19th World Congress of the International Federation of Automatic Control, Cape Town, Souh Africa, August 2014.

  • 68J. L. Avila Alonso, C. Bonnet, H. Ozbay, J. Clairambault, S.-I. Niculescu.

    A discrete-maturity Interconnected Model of Healthy and Cancer Cell Dynamics in Acute Myeloid Leukemia, in: Mathematical Theory of Networks and Systems, Groningen, Netherlands, July 2014.

  • 69H. T. Banks, M. Doumic, C. Kruse, S. Prigent, H. Rezaei.

    Information Content in Data Sets for a Nucleated-Polymerization Model, in: Journal of Biological Dynamics, June 2015, vol. 9, no 1, 26 p. [ DOI : 10.1080/17513758.2015.1050465 ]

  • 70H. T. Banks, M. Doumic-Jauffret, C. Kruse.

    A numerical scheme for the early steps of nucleation-aggregation Models, in: Journal of Mathematical Biology, January 2017, vol. 74, no 1-2, pp. 259-287. [ DOI : 10.1007/s00285-016-1026-0 ]

  • 71J. Barré, J. A. Carillo, P. Degond, E. Zatorska, D. Peurichard.

    Particle interactions mediated by dynamical networks: assessment of macroscopic descriptions, in: Journal of Nonlinear Science, 2017.
  • 72J. Barré, P. Degond, E. Zatorska, D. Peurichard.

    Modelling pattern formation through differential repulsion, in: Networks and Heterogeneous media, 2019, to appear.
  • 73F. Bekkal Brikci, J. Clairambault, B. Perthame.

    Analysis of a molecular structured population model with possible polynomial growth for the cell division cycle, in: Math. Comput. Modelling, 2008, vol. 47, no 7-8, pp. 699–713.
  • 74F. Bertaux, S. Stoma, D. Drasdo, G. Batt.

    Modeling Dynamics of Cell-to-Cell Variability in TRAIL-Induced Apoptosis Explains Fractional Killing and Predicts Reversible Resistance, in: PLoS Computational Biology, 2014, vol. 10, no 10, 14 p. [ DOI : 10.1371/journal.pcbi.1003893.s016 ]

  • 75J. Bertoin, A. R. Watson.

    Probabilistic aspects of critical growth-fragmentation equations, in: Advances in Applied Probability, 9 2015.
  • 76P.-A. Bliman, M. S. Aronna, F. C. Coelho, M. A. H. B. da Silva.

    Ensuring successful introduction of Wolbachia in natural populations of Aedes aegypti by means of feedback control, in: Journal of Mathematical Biology, August 2017. [ DOI : 10.1007/s00285-017-1174-x ]

  • 77C. Bonnet, J. L. Avila Alonso, H. Ozbay, J. Clairambault, S.-I. Niculescu, P. Hirsch.

    A Discrete-Maturity Interconnected Model of Healthy and Cancer Cell Dynamics in Acute Myeloid Leukemia, in: The 10th AIMS Conference on Dynamical Systems,Differential Equations and Applications, Madrid, Spain, July 2014.

  • 78T. Bourgeron, M. Doumic, M. Escobedo.

    Estimating the division rate of the growth-fragmentation equation with a self-similar kernel, in: Inverse Problems, Jan 2014, vol. 30, no 2, 025007 p.

  • 79T. Bourgeron, Z. Xu, M. Doumic, M. T. Teixeira.

    The asymmetry of telomere replication contributes to replicative senescence heterogeneity, in: Scientific Reports, October 2015, vol. 5, 15326 p. [ DOI : 10.1038/srep15326 ]

  • 80K. Bourtzis.

    Wolbachia-Based Technologies for Insect Pest Population Control, in: Advances in Experimental Medicine and Biology, Springer, New York, NY, 02 2008, vol. 627.
  • 81A. Brown.

    Insecticide resistance in mosquitoes: a pragmatic review., in: Journal of the American Mosquito Control Association, 1986, vol. 2, no 2, pp. 123–140.
  • 82F. Bubba, C. Pouchol, N. Ferrand, G. Vidal, L. Almeida, B. Perthame, M. Sabbah.

    A chemotaxis-based explanation of spheroid formation in 3D cultures of breast cancer cells, in: Journal of Theoretical Biology, 2019, vol. 479, pp. 73-80. [ DOI : 10.1016/j.jtbi.2019.07.002 ]

  • 83M. J. Caceres, B. Perthame.

    Beyond blow-up in excitatory integrate and fire neuronal networks: refractory period and spontaneous activity, in: Journal of Theoretical Biology, 2014, vol. 350, pp. 81-89. [ DOI : 10.1016/j.jtbi.2014.02.005 ]

  • 84V. Calvez, M. Doumic, P. Gabriel.

    Self-similarity in a general aggregation–fragmentation problem. Application to fitness analysis, in: Journal de Mathématiques Pures et Appliquées, 2012, vol. 98, no 1, pp. 1 - 27. [ DOI : 10.1016/j.matpur.2012.01.004 ]

  • 85V. Calvez, N. Lenuzza, M. Doumic, J.-P. Deslys, F. Mouthon, B. Perthame.

    Prion dynamic with size dependency - strain phenomena, in: J. of Biol. Dyn., 2010, vol. 4, no 1, pp. 28–42.
  • 86V. Calvez, B. Perthame, S. Yasuda.

    Traveling Wave and Aggregation in a Flux-Limited Keller-Segel Model, in: Kinetic and Related Models , 2018, vol. 11, no 4, pp. 891–909. [ DOI : 10.3934/krm.2018035 ]

  • 87J. A. Carrillo, F. James, F. Lagoutière, N. Vauchelet.

    The Filippov characteristic flow for the aggregation equation with mildly singular potentials, in: Journal of Differential Equations, 2016, vol. 260, no 1, pp. 304-338, 33 pages.

  • 88G. Cellière.

    Multi-scale modeling of hepatic drug toxicity and its consequences on ammonia detoxification, Université Paris 6 - Pierre et Marie Curie, July 2017.
  • 89J. Chevallier, M. J. Caceres, M. Doumic, P. Reynaud-Bouret.

    Microscopic approach of a time elapsed neural model, in: Mathematical Models and Methods in Applied Sciences, December 2015, 2669 p. [ DOI : 10.1142/S021820251550058X ]

  • 90R. H. Chisholm, T. Lorenzi, J. Clairambault.

    Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation, in: BBA - General Subjects, June 2016, vol. 1860, pp. 2627 - 2645. [ DOI : 10.1016/j.bbagen.2016.06.009 ]

  • 91R. H. Chisholm, T. Lorenzi, A. Lorz, A. K. Larsen, L. N. d. Almeida, A. Escargueil, J. Clairambault.

    Emergence of Drug Tolerance in Cancer Cell Populations: An Evolutionary Outcome of Selection, Nongenetic Instability, and Stress-Induced Adaptation, in: Cancer Research, Jan 2015, vol. 75, no 6, pp. 930–939. [ DOI : 10.1158/0008-5472.can-14-2103 ]

  • 92R. H. Chisholm, T. Lorenzi, A. Lorz, A. K. Larsen, L. N. de Almeida, A. Escargueil, J. Clairambault.

    Emergence of Drug Tolerance in Cancer Cell Populations: An Evolutionary Outcome of Selection, Nongenetic Instability, and Stress-Induced Adaptation, in: Cancer Research, March 2015, vol. 75, no 6, pp. 930-939. [ DOI : 10.1158/0008-5472.CAN-14-2103 ]

  • 93W. Djema, C. Bonnet, F. Mazenc, J. Clairambault, E. Fridman, P. Hirsch, F. Delhommeau.

    Control in dormancy or eradication of cancer stem cells: Mathematical modeling and stability issues, in: Journal of Theoretical Biology, July 2018, vol. 449, pp. 103 - 123. [ DOI : 10.1016/j.jtbi.2018.03.038 ]

  • 94W. Djema, F. Mazenc, C. Bonnet, J. Clairambault, E. Fridman.

    Stability Analysis of a Nonlinear System with Infinite Distributed Delays Describing Cell Dynamics, in: IEEE American Control Conference (ACC 2018), Milwaukee, United States, June 2018. [ DOI : 10.23919/acc.2018.8430869 ]

  • 95W. Djema, F. Mazenc, C. Bonnet, J. Clairambault, P. Hirsch, F. Delhommeau.

    Stability of a Delay System Coupled to a Differential-Difference System Describing the Coexistence of Ordinary and Mutated Hematopoietic Stem Cells, in: Conference on Decision and Control , Las Vegas, United States, December 2016.

  • 96M. Doumic, M. Escobedo.

    Time Asymptotics for a Critical Case in Fragmentation and Growth-Fragmentation Equations, in: Kinetic and Related Models , June 2016, vol. 9, no 2, 47 p. [ DOI : 10.3934/krm.2016.9.251 ]

  • 97M. Doumic, M. Escobedo, M. Tournus.

    Estimating the division rate and kernel in the fragmentation equation, in: Annales de l'Institut Henri Poincaré (C) Non Linear Analysis, 2018, https://arxiv.org/abs/1804.08945, forthcoming. [ DOI : 10.1016/j.anihpc.2018.03.004 ]

  • 98M. Doumic, S. Eugene, P. Robert.

    Asymptotics of Stochastic Protein Assembly Models, in: SIAM Journal on Applied Mathematics, November 2016, vol. 76, no 6, 20 p. [ DOI : 10.1137/16M1066920 ]

  • 99M. Doumic, P. Gabriel.

    Eigenelements of a General Aggregation-Fragmentation Model, in: Mathematical Models and Methods in Applied Sciences, 2009, vol. 20, no 05, 757 p.

  • 100M. Doumic, M. Hoffmann, N. Krell, L. Robert.

    Statistical estimation of a growth-fragmentation model observed on a genealogical tree, October 2012, 46 pages, 4 figures.

  • 101M. Doumic, B. Perthame, J. Zubelli.

    Numerical Solution of an Inverse Problem in Size-Structured Population Dynamics, in: Inverse Problems, 2009, vol. 25, no 4, 045008 p.
  • 102D. Drasdo, A. Buttenschön, P. Van Liedekerke.

    Agent-Based Lattice Models of Multicellular Systems, in: Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes, Elsevier, 2018, pp. 223-238. [ DOI : 10.1016/B978-0-12-811718-7.00012-5 ]

  • 103D. Drasdo, S. Hoehme, J. G. Hengstler.

    How predictive quantitative modeling of tissue organization can inform liver disease pathogenesis, in: Journal of Hepatology, October 2014, vol. 61, no 4, pp. 951–956. [ DOI : 10.1016/j.jhep.2014.06.013 ]

  • 104V. A. Dyck, J. Hendrichs, A. S. Robinson.

    The Sterile Insect Technique, Principles and Practice in Area-Wide Integrated Pest Management, Springer, Dordrecht, 2006, 787 p.
  • 105S. Eugene.

    Stochastic modelling in molecular biology: a probabilistic analysis of protein polymerisation and telomere shortening, UPMC LJLL, September 2016.

  • 106S. Eugene, W.-F. Xue, P. Robert, M. Doumic-Jauffret.

    Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly, in: Journal of Chemical Physics, May 2016, vol. 144, no 17, 12 p. [ DOI : 10.1063/1.4947472 ]

  • 107A. Ghallab, G. Cellière, S. Henkel, D. Driesch, S. Hoehme, U. Hofmann, S. Zellmer, P. Godoy, A. Sachinidis, M. Blaszkewicz, R. Reif, R. Marchan, L. Kuepfer, D. Häussinger, D. Drasdo, G. Gebhardt, J. G. Hengstler.

    Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases, in: Journal of Hepatology, November 2015, vol. 64, no 4, pp. 860–871. [ DOI : 10.1016/j.jhep.2015.11.018 ]

  • 108A. Ghallab, U. Hofmann, S. Sezgin, N. Vartak, R. Hassan, A. Zaza, P. Godoy, K. M. Schneider, G. Guenther, Y. A. Ahmed, A. Abbas, V. Keitel, L. Kuepfer, S. Dooley, F. Lammert, C. Trautwein, M. Spiteller, D. Drasdo, A. Hofmann, P. L. Jansen, J. Hengstler, R. Reif.

    Bile Microinfarcts in Cholestasis Are Initiated by Rupture of the Apical Hepatocyte Membrane and Cause Shunting of Bile to Sinusoidal Blood, in: Hepatology, August 2018.

  • 109L. Gosse, N. Vauchelet.

    Hydrodynamic singular regimes in 1+1 kinetic models and spectral numerical methods, in: Journal of Mathematical Analysis and Applications, 2016. [ DOI : 10.1016/j.jmaa.2016.07.059 ]

  • 110J. Hemingway, H. Ranson.

    Insecticide resistance in insect vectors of human disease, in: Annual review of entomology, 2000, vol. 45, no 1, pp. 371–391.
  • 111M. Hertig, S. B. Wolbach.

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