EN FR
EN FR
MAMBA - 2018


Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 6R. Aghajani, P. Robert, W. Sun.

    A Large Scale Analysis of Unreliable Stochastic Networks, in: The Annals of Applied Probability : an official journal of the institute of mathematical statistics, April 2018, vol. 28, no 2, 36 p, https://arxiv.org/abs/1608.08743. [ DOI : 10.1214/17-AAP1318 ]

    https://hal.archives-ouvertes.fr/hal-01359208
  • 7V. 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, https://arxiv.org/abs/1709.07296. [ DOI : 10.3934/krm.2018035 ]

    https://hal.sorbonne-universite.fr/hal-01591490
  • 8J. Calvo, M. Doumic, B. Perthame.

    Long-time asymptotics for polymerization models, in: Communications in Mathematical Physics, October 2018, vol. 363, no 1, pp. 111-137, https://arxiv.org/abs/1707.09777. [ DOI : 10.1007/s00220-018-3218-5 ]

    https://hal.archives-ouvertes.fr/hal-01570292
  • 9T. Chagas, P.-A. Bliman, K. Kienitz.

    Stabilization of periodic orbits of discrete-time dynamical systems using the Prediction-Based Control: New control law and practical aspects, in: Journal of The Franklin Institute, August 2018, vol. 355, no 12, pp. 4771-4793. [ DOI : 10.1016/j.jfranklin.2018.04.040 ]

    https://hal.inria.fr/hal-01941693
  • 10T. P. Chagas, P.-A. Bliman, K. H. Kienitz.

    Approximate Prediction-Based Control Method for Nonlinear Oscillatory Systems with Applications to Chaotic Systems, in: Journal of Control Science and Engineering, March 2018, vol. 2018, pp. 1-29. [ DOI : 10.1155/2018/3298286 ]

    https://hal.inria.fr/hal-01722175
  • 11J. Clairambault, B. Perthame, A. Quillas Maran.

    Analysis of a system describing proliferative-quiescent cell dynamics, in: Chinese Annals of Mathematics - Series B, 2018, pp. 1-13.

    https://hal.sorbonne-universite.fr/hal-01674142
  • 12W. 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 ]

    https://hal.inria.fr/hal-01852154
  • 13M. 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. [ DOI : 10.1016/j.anihpc.2018.03.004 ]

    https://hal.archives-ouvertes.fr/hal-01501811
  • 14A. 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.

    https://hal.inria.fr/hal-01968843
  • 15S. Hoehme, F. Bertaux, W. Weens, B. Grasl-Kraupp, J. Hengstler, D. Drasdo.

    Model Prediction and Validation of an Order Mechanism Controlling the Spatiotemporal Phenotype of Early Hepatocellular Carcinoma, in: Bulletin of Mathematical Biology, May 2018, vol. 80, no 5, pp. 1134-1171.

    https://hal.inria.fr/hal-01968844
  • 16L. Neves de 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 ]

    https://hal.archives-ouvertes.fr/hal-01745769
  • 17S. Nordmann, B. Perthame, C. Taing.

    Dynamics of concentration in a population model structured by age and a phenotypical trait, in: Acta Applicandae Mathematicae, June 2018, vol. 155, no 1. [ DOI : 10.1007/s10440-017-0151-0 ]

    https://hal.archives-ouvertes.fr/hal-01493068
  • 18G. Peeters, C. Debbaut, A. Friebel, P. Cornillie, W. De Vos, K. Favere, I. Vander Elst, T. Vandecasteele, T. Johann, L. Van Hoorebeke, D. Monbaliu, D. Drasdo, S. Hoehme, W. Laleman, P. Segers.

    Quantitative analysis of hepatic macro- and microvascular alterations during cirrhogenesis in the rat, in: Journal of Anatomy, 2018. [ DOI : 10.1111/joa.12760 ]

    https://hal.inria.fr/hal-01700102
  • 19B. Perthame, E. Ribes, D. Salort.

    Career plans and wage structures: a mean field game approach, in: Mathematics in Engineering, May 2018, vol. 1, no 1, pp. 47-63. [ DOI : 10.3934/Mine.2018.1.47 ]

    https://hal.sorbonne-universite.fr/hal-01674630
  • 20B. Perthame, W. Sun, M. Tang.

    The fractional diffusion limit of a kinetic model with biochemical pathway, in: Zeitschrift für Angewandte Mathematik und Physik, May 2018, vol. 69:67, https://arxiv.org/abs/1709.03308. [ DOI : 10.1007/s00033-018-0964-3 ]

    https://hal.sorbonne-universite.fr/hal-01584754
  • 21B. Perthame, S. Yasuda.

    Stiff-response-induced instability for chemotactic bacteria and flux-limited Keller-Segel equation, in: Nonlinearity, 2018, vol. 31, no 9. [ DOI : 10.1088/1361-6544/aac760 ]

    https://hal.sorbonne-universite.fr/hal-01494963
  • 22C. Pouchol, J. Clairambault, A. Lorz, E. Trélat.

    Asymptotic analysis and optimal control of an integro-differential system modelling healthy and cancer cells exposed to chemotherapy, in: Journal de Mathématiques Pures et Appliquées, 2018, vol. 116, pp. 268–308, https://arxiv.org/abs/1612.04698. [ DOI : 10.1016/j.matpur.2017.10.007 ]

    https://hal.archives-ouvertes.fr/hal-01673589
  • 23C. Pouchol, E. Trélat.

    Global stability with selection in integro-differential Lotka-Volterra systems modelling trait-structured populations, in: Journal of Biological Dynamics, 2018, vol. 12, no 1, pp. 872–893, https://arxiv.org/abs/1702.06187.

    https://hal.archives-ouvertes.fr/hal-01470722
  • 24P. Robert, A. Veber.

    A Scaling Analysis of a Star Network with Logarithmic Weights, in: Stochastic Processes and their Applications, June 2018, https://arxiv.org/abs/1609.04180.

    https://hal.inria.fr/hal-01377703
  • 25W. Sun.

    A Functional Central Limit Theorem for the Becker-Döring model, in: Journal of Statistical Physics, 2018, vol. 171, no 1, pp. 145–165, https://arxiv.org/abs/1710.04059 - 18 pages. [ DOI : 10.04059 ]

    https://hal.inria.fr/hal-01616039

International Conferences with Proceedings

  • 26M. S. Aronna, P.-A. Bliman.

    Interval observer for uncertain time-varying SIR-SI epidemiological model of vector-borne disease, in: ECC 2018 - European Control Conference, Limassol, Cyprus, June 2018, pp. 1-6, https://arxiv.org/abs/1703.07083.

    https://hal.inria.fr/hal-01493078
  • 27P.-A. Bliman, D. Efimov, R. Ushirobira.

    A class of nonlinear adaptive observers for SIR epidemic model, in: ECC 2018 - European Control Conference, Limassol, Cyprus, June 2018, 6 p.

    https://hal.inria.fr/hal-01724989
  • 28W. Djema, C. Bonnet, F. Mazenc, J. Clairambault.

    Introducing Cell-Plasticity Mechanisms into a Class of Cell Population Dynamical Systems, in: IEEE American Control Conference (ACC 2018), Milwaukee, United States, June 2018. [ DOI : 10.23919/acc.2018.8430758 ]

    https://hal.inria.fr/hal-01848890
  • 29W. 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 ]

    https://hal.inria.fr/hal-01849010

Scientific Books (or Scientific Book chapters)

  • 30D. 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 ]

    https://hal.inria.fr/hal-01968847
  • 31L. Neves de 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.

    https://hal.inria.fr/hal-01945593
  • 32P. Van Liedekerke, A. Buttenschön, D. Drasdo.

    Off-Lattice Agent-Based Models for Cell and Tumor Growth, in: Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes, Elsevier, 2018, pp. 245-267. [ DOI : 10.1016/B978-0-12-811718-7.00014-9 ]

    https://hal.inria.fr/hal-01968846

Books or Proceedings Editing

Other Publications

References in notes
  • 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.

    https://hal.inria.fr/tel-01447286
  • 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 ]

    https://hal.archives-ouvertes.fr/hal-01248255
  • 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 ]

    https://hal.archives-ouvertes.fr/hal-01574346
  • 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 ]

    https://hal.inria.fr/hal-00932779
  • 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.

    https://hal.inria.fr/hal-01110304
  • 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.

    https://hal.inria.fr/hal-00940245
  • 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.

    https://hal.inria.fr/hal-00940305
  • 69H. T. Banks, M. Doumic, 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 ]

    https://hal.inria.fr/hal-00954437
  • 70H. 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 ]

    https://hal.inria.fr/hal-01123847
  • 71J. Barré, J. A. Carrillo, 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, A. Khuong, E. Zatorska, D. Peurichard.

    A two-species macroscopic model for cell segregation and border sharpening by Eph receptor ephrin-mediated repulsion, in: to be submitted, 2019.
  • 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 ]

    https://hal.inria.fr/hal-00942885
  • 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 ]

    https://hal.inria.fr/hal-01579477
  • 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.

    https://hal.inria.fr/hal-01110309
  • 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.

    http://dx.doi.org/10.1088/0266-5611/30/2/025007
  • 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 ]

    http://hal.upmc.fr/hal-01272075
  • 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.
  • 82P. O. Bucur, M. Bekheit, C. Audebert, A. Othman, S. Hammad, M. Sebagh, M. A. Allard, B. Decante, A. Friebel, D. Drasdo, E. Miquelestorena-Standley, J. G. Hengstler, I. Vignon-Clementel, E. Vibert.

    Modulating Portal Hemodynamics With Vascular Ring Allows Efficient Regeneration After Partial Hepatectomy in a Porcine Model., in: Annals of Surgery, February 2017. [ DOI : 10.1097/SLA.0000000000002146 ]

    https://hal.archives-ouvertes.fr/hal-01494844
  • 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 ]

    http://hal.upmc.fr/hal-00874746
  • 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 ]

    http://www.sciencedirect.com/science/article/pii/S002178241200013X
  • 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.
  • 86J. 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.

    https://hal.archives-ouvertes.fr/hal-01061991
  • 87J. 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 ]

    http://hal.upmc.fr/hal-01159215
  • 88R. 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 ]

    https://hal.inria.fr/hal-01321535
  • 89R. H. Chisholm, T. Lorenzi, A. Lorz, A. K. Larsen, L. Neves 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 ]

    https://hal.inria.fr/hal-01237893
  • 90R. H. Chisholm, T. Lorenzi, A. Lorz, A. K. Larsen, L. Neves 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, Jan 2015, vol. 75, no 6, pp. 930–939. [ DOI : 10.1158/0008-5472.can-14-2103 ]

    http://dx.doi.org/10.1158/0008-5472.CAN-14-2103
  • 91W. 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.

    https://hal.inria.fr/hal-01389870
  • 92M. 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 ]

    https://hal.inria.fr/hal-01080361
  • 93M. 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 ]

    https://hal.inria.fr/hal-01301266
  • 94M. 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.

    http://arxiv.org/abs/0907.5467
  • 95M. 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.

    https://hal.archives-ouvertes.fr/hal-00763601
  • 96M. 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.
  • 97D. 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 ]

    https://hal.inria.fr/hal-01110644
  • 98V. 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.
  • 99S. Eugene.

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

    https://hal.inria.fr/tel-01377561
  • 100S. Eugene, W.-F. Xue, P. Robert, M. Doumic.

    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 ]

    https://hal.inria.fr/hal-01205549
  • 101A. 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 ]

    https://hal.archives-ouvertes.fr/hal-01257127
  • 102L. 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 ]

    https://hal.archives-ouvertes.fr/hal-01354980
  • 103J. Hemingway, H. Ranson.

    Insecticide resistance in insect vectors of human disease, in: Annual review of entomology, 2000, vol. 45, no 1, pp. 371–391.
  • 104M. Hertig, S. B. Wolbach.

    Studies on rickettsia-like micro-organisms in insects, in: The Journal of medical research, 1924, vol. 44, no 3, 329 p.
  • 105V. H. Hoang.

    Adaptive estimation for inverse problems with applications to cell divisions, Université de Lille 1 – Sciences et Technologies, November 2016.

    https://tel.archives-ouvertes.fr/tel-01417780
  • 106M. Hoffmann, A. Olivier.

    Nonparametric estimation of the division rate of an age dependent branching process, in: Stochastic Processes and their Applications, December 2015. [ DOI : 10.1016/j.spa.2015.11.009 ]

    https://hal.archives-ouvertes.fr/hal-01254203
  • 107N. Jagiella, B. Müller, M. Müller, I. E. Vignon-Clementel, D. Drasdo.

    Inferring Growth Control Mechanisms in Growing Multi-cellular Spheroids of NSCLC Cells from Spatial-Temporal Image Data, in: PLoS Computational Biology, 2016, vol. 12, no 2, e1004412 p. [ DOI : 10.1371/journal.pcbi.1004412 ]

    http://hal.upmc.fr/hal-01244593
  • 108F. James, N. Vauchelet.

    Numerical methods for one-dimensional aggregation equations, in: SIAM Journal on Numerical Analysis, 2015, vol. 53, no 2, pp. 895-916. [ DOI : 10.1137/140959997 ]

    https://hal.archives-ouvertes.fr/hal-00955971
  • 109F. James, N. Vauchelet.

    Equivalence between duality and gradient flow solutions for one-dimensional aggregation equations, in: Discrete and Continuous Dynamical Systems - Series A, 2016, vol. 36, no 3, pp. 1355-1382.

    https://hal.archives-ouvertes.fr/hal-00803709
  • 110G. Jankowiak, D. Peurichard, A. Reversat, M. Sixt, C. Schmeiser.

    Modelling adhesion-independent cell migration, in: to be submitted, 2019.
  • 111M.-J. Kang, B. Perthame, D. Salort.

    Dynamics of time elapsed inhomogeneous neuron network model, in: Comptes Rendus Mathématique, September 2015, no 353, pp. 1111-1115. [ DOI : 10.1016/j.crma.2015.09.029 ]

    http://hal.upmc.fr/hal-01241300
  • 112J. Kean, S. Rainey, M. McFarlane, C. Donald, E. Schnettler, A. Kohl, E. Pondeville.

    Fighting arbovirus transmission: natural and engineered control of vector competence in Aedes mosquitoes, in: Insects, 2015, vol. 6, no 1, pp. 236–278.
  • 113I. C. Kim, B. Perthame, P. E. Souganidis.

    Free boundary problems for tumor growth: a viscosity solutions approach, in: Nonlinear Analysis: Theory, Methods and Applications, 2016, vol. 138, pp. 207-228. [ DOI : 10.1016/j.na.2016.01.019 ]

    http://hal.upmc.fr/hal-01155696
  • 114M. Kolwalczyk, B. Perthame, N. Vauchelet.

    Transversal instability for the thermodiffusive reaction-diffusion system, in: Chinese Annals of Mathematics - Series B, 2015, vol. 36, no 5, pp. 871-882, 13 pages.

    https://hal.archives-ouvertes.fr/hal-00939013
  • 115T. Lorenzi, R. H. Chisholm, J. Clairambault.

    Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations, in: Biology Direct, December 2016, vol. 11, no 1, 43 p. [ DOI : 10.1186/s13062-016-0143-4 ]

    https://hal.inria.fr/hal-01355314
  • 116T. Lorenzi, R. H. Chisholm, L. Desvillettes, B. D. Hughes.

    Dissecting the dynamics of epigenetic changes in phenotype-structured populations exposed to fluctuating environments, in: Journal of Theoretical Biology, September 2015, vol. 386, pp. 166-176. [ DOI : 10.1016/j.jtbi.2015.08.031 ]

    https://hal.inria.fr/hal-01237890
  • 117T. Lorenzi, R. H. Chisholm, A. Lorz.

    Effects of an advection term in nonlocal Lotka-Volterra equations, December 2015.

    https://hal.archives-ouvertes.fr/hal-01237529
  • 118A. Lorz, T. Lorenzi, J. Clairambault, A. Escargueil, B. Perthame.

    Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors, in: Bulletin of Mathematical Biology, January 2015, vol. 77, no 1, pp. 1-22. [ DOI : 10.1007/s11538-014-0046-4 ]

    http://hal.upmc.fr/hal-00921266
  • 119A. Lorz, T. Lorenzi, M. E. Hochberg, J. Clairambault, B. Perthame.

    Populational adaptive evolution, chemotherapeutic resistance and multiple anti-cancer therapies, in: ESAIM: Mathematical Modelling and Numerical Analysis, March 2013, 23 p. [ DOI : 10.1051/m2an/2012031 ]

    https://hal.archives-ouvertes.fr/hal-00714274
  • 120A. Mellet, B. Perthame, F. Quirós.

    A Hele-Shaw Problem for Tumor Growth, December 2015, working paper or preprint.

    http://hal.upmc.fr/hal-01241309
  • 121L. A. Moreira, I. Iturbe-Ormaetxe, J. A. Jeffery, G. Lu, A. T. Pyke, L. M. Hedges, B. C. Rocha, S. Hall-Mendelin, A. Day, M. Riegler, L. E. Hugo, K. N. Johnson, B. H. Kay, E. A. McGraw, A. F. van den Hurk, P. A. Ryan, S. L. O'Neill.

    A Wolbachia Symbiont in Aedes aegypti Limits Infection with Dengue, Chikungunya, and Plasmodium, in: Cell, 2009, vol. 139, no 7, pp. 1268 - 1278.
  • 122A. Olivier.

    Statistical analysis of growth-fragmentation models, Université Paris Dauphine - Paris IX, November 2015.

    https://hal.archives-ouvertes.fr/tel-01235239
  • 123A. Olivier.

    How does variability in cells aging and growth rates influence the malthus parameter?, in: Kinetic and Related Models , June 2017, vol. 10, no 2, pp. 481-512. [ DOI : 10.3934/krm.2017019 ]

    https://hal.archives-ouvertes.fr/hal-01274529
  • 124K. Pakdaman, B. Perthame, D. Salort.

    Adaptation and Fatigue Model for Neuron Networks and Large Time Asymptotics in a Nonlinear Fragmentation Equation, in: Journal of Mathematical Neuroscience, 2014, vol. 4, no 1, 14 p. [ DOI : 10.1186/2190-8567-4-14 ]

    https://hal.inria.fr/hal-01054561
  • 125G. Peeters, C. Debbaut, W. Laleman, A. Friebel, D. Monbaliu, I. Vander Elst, J. R. Detrez, T. Vandecasteele, T. Johann, T. De Schryver, L. Van Hoorebeke, K. Favere, J. Verbeke, D. Drasdo, S. Hoehme, P. Segers, P. Cornillie, W. H. De Vos.

    Corrigendum, in: Journal of Anatomy, November 2017, vol. 231, no 5, pp. 786-786. [ DOI : 10.1111/joa.12723 ]

    https://hal.inria.fr/hal-01968855
  • 126B. Perthame.

    Transport equations in biology, Frontiers in Mathematics, Birkhäuser Verlag, Basel, 2007, x+198 p.
  • 127B. Perthame, F. Quirós, M. Tang, N. Vauchelet.

    Derivation of a Hele-Shaw type system from a cell model with active motion, July 2013.

    http://hal.upmc.fr/hal-00906168
  • 128B. Perthame, F. Quirós, J.-L. Vázquez.

    The Hele-Shaw asymptotics for mechanical models of tumor growth, in: Archive for Rational Mechanics and Analysis, 2014, vol. 212, pp. 93-127. [ DOI : 10.1007/s00205-013-0704-y ]

    http://hal.upmc.fr/hal-00831932
  • 129B. Perthame, D. Salort.

    On a voltage-conductance kinetic system for integrate and fire neural networks, in: Kinetic and Related Models , December 2013, vol. 6, no 4, pp. 841-864. [ DOI : 10.3934/krm.2013.6.841 ]

    http://hal.upmc.fr/hal-00871609
  • 130B. Perthame, D. Salort, G. Wainrib.

    Distributed synaptic weights in a LIF neural network and learning rules, in: Physica D: Nonlinear Phenomena, 2017, vol. 353-354, pp. 20-30. [ DOI : 10.1016/j.physd.2017.05.005 ]

    http://hal.upmc.fr/hal-01541093
  • 131B. Perthame, M. Tang, N. Vauchelet.

    Traveling wave solution of the Hele-Shaw model of tumor growth with nutrient, in: Mathematical Models and Methods in Applied Sciences, 2014, vol. 24, no 13, pp. 2601-2626, 25 pages.

    https://hal.archives-ouvertes.fr/hal-00931399
  • 132B. Perthame, N. Vauchelet.

    Incompressible limit of mechanical model of tumor growth with viscosity, in: Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences (1934–1990), 2015, vol. 373, 20140283 p, 16 pages. [ DOI : 10.1098/rsta.2014.0283 ]

    https://hal.archives-ouvertes.fr/hal-01066494
  • 133B. Perthame, J. Zubelli.

    On the inverse problem for a size-structured population model, in: Inverse Problems, 2007, vol. 23, no 3, pp. 1037–1052.
  • 134D. Peurichard, e. al.

    Simple mechanical cues could explain adipose tissue morphology, in: J. Theor Biol, 2017.

    https://doi.org/10.1016/j.jtbi.2017.06.030
  • 135D. Peurichard, e. al.

    Extra-cellular matrix rigidity may dictate the fate of injury outcome, in: J. Theor Biol (to appear), 2019.
  • 136C. Pouchol, J. Clairambault, A. Lorz, E. Trélat.

    Asymptotic analysis and optimal control of an integro-differential system modelling healthy and cancer cells exposed to chemotherapy, December 2016, accepted in the J. Math. Pures et App..

    https://hal.archives-ouvertes.fr/hal-01416594
  • 137S. Prigent, A. Ballesta, F. Charles, N. Lenuzza, P. Gabriel, L. M. Tine, H. Rezaei, M. Doumic.

    An efficient kinetic model for assemblies of amyloid fibrils and its application to polyglutamine aggregation., in: PLoS ONE, 2012, vol. 7, no 11, e43273 p. [ DOI : 10.1371/journal.pone.0043273 ]

    https://hal.archives-ouvertes.fr/hal-00778052
  • 138L. Robert, M. Hoffmann, N. Krell, S. Aymerich, J. Robert, M. Doumic.

    Division in Escherichia coli is triggered by a size-sensing rather than a timing mechanism, in: BMC Biology, 2014, vol. 12, no 1, 17 p. [ DOI : 10.1186/1741-7007-12-17 ]

    https://hal.inria.fr/hal-00981312
  • 139F. Schliess, S. Hoehme, S. Henkel, A. Ghallab, D. Driesch, J. Böttger, R. Guthke, M. Pfaff, J. Hengstler, R. Gebhardt, D. Häussinger, D. Drasdo, S. Zellmer.

    Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration, in: Hepatology, December 2014, vol. 60, no 6, pp. 2040–2051. [ DOI : 10.1002/hep.27136 ]

    https://hal.inria.fr/hal-01110646
  • 140N. Sfakianakis, D. Peurichard, A. Brunk, C. Schmeiser.

    Modelling cell-cell collision and adhesion with the Filament Based Lamellipodium Model, in: BIOMATH, 2019.

    http://dx.doi.org/10.11145/j.biomath.2018.11.097
  • 141S. P. Sinkins.

    Wolbachia and cytoplasmic incompatibility in mosquitoes, in: Insect Biochemistry and Molecular Biology, 2004, vol. 34, no 7, pp. 723 - 729, Molecular and population biology of mosquitoes.
  • 142P. Van Liedekerke, J. Neitsch, T. Johann, K. Alessandri, P. Nassoy, D. Drasdo.

    Quantitative modeling identifies robust predictable stress response of growing CT26 tumor spheroids under variable conditions, December 2016, working paper or preprint.

    https://hal.inria.fr/hal-01421179
  • 143P. Van Liedekerke, M. M. Palm, N. Jagiella, D. Drasdo.

    Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results, in: Computational Particle Mechanics, Nov 2015, vol. 2, no 4, pp. 401–444.

    http://dx.doi.org/10.1007/s40571-015-0082-3
  • 144T. Walker, S. P. Sinkins.

    Biological control of arbovirus vectors, in: Arboviruses: Molecular Biology, Evolution and Control. Caister Academic Press, Norfolk, UK, 2016, pp. 291–302.
  • 145Y. Yin, O. Sedlaczek, B. Müller, A. Warth, M. González-Vallinas, B. Lahrmann, N. Grabe, H.-U. Kauczor, K. Breuhahn, I. Vignon-Clementel, D. Drasdo.

    Tumor cell load and heterogeneity estimation from diffusion-weighted MRI calibrated with histological data: an example from lung cancer, in: IEEE Transactions on Medical Imaging, 2017. [ DOI : 10.1109/TMI.2017.2698525 ]

    https://hal.inria.fr/hal-01421398