An investigation on Monod-Haldane immune response based tumor-effector-interleukin-2 interactions with treatments
暂无分享,去创建一个
Parthasakha Das | Samhita Das | Pritha Das | Samhita Das | P. Das | P. Das
[1] E. Coddington,et al. Theory of Ordinary Differential Equations , 1955 .
[2] Lansun Chen,et al. Permanence and positive periodic solution for the single-species nonautonomous delay diffusive models , 1996 .
[3] Jun Tanimoto,et al. Analysis of SIR epidemic model with information spreading of awareness , 2019, Chaos, Solitons & Fractals.
[4] Magda Galach,et al. DYNAMICS OF THE TUMOR—IMMUNE SYSTEM COMPETITION—THE EFFECT OF TIME DELAY , 2003 .
[5] D. Kirschner,et al. A methodology for performing global uncertainty and sensitivity analysis in systems biology. , 2008, Journal of theoretical biology.
[6] L. Coussens,et al. Paradoxical roles of the immune system during cancer development , 2006, Nature Reviews Cancer.
[7] A. Radunskaya,et al. Mixed Immunotherapy and Chemotherapy of Tumors: Modeling, Applications and Biological Interpretations , 2022 .
[8] W. Leonard,et al. Interleukin-2 at the crossroads of effector responses, tolerance, and immunotherapy. , 2013, Immunity.
[9] Kwang Su Kim,et al. Optimal Treatment Strategy for a Tumor Model under Immune Suppression , 2014, Comput. Math. Methods Medicine.
[10] D. Earn,et al. Interactions Between the Immune System and Cancer: A Brief Review of Non-spatial Mathematical Models , 2011, Bulletin of mathematical biology.
[11] Sandip Banerjee,et al. Stability and bifurcation analysis of delay induced tumor immune interaction model , 2014, Appl. Math. Comput..
[12] Chuncheng Wang,et al. Sensitivity and uncertainty analysis of a simplified Kirschner-Panetta model for immunotherapy of tumor-immune interaction , 2015, Advances in Difference Equations.
[13] P. Hahnfeldt,et al. Immunoediting: evidence of the multifaceted role of the immune system in self-metastatic tumor growth , 2012, Theoretical Biology and Medical Modelling.
[14] D. Noonan,et al. Tumor inflammatory angiogenesis and its chemoprevention. , 2005, Cancer research.
[15] Franz Kappel,et al. Time delay in physiological systems: analyzing and modeling its impact. , 2011, Mathematical biosciences.
[16] Dibakar Ghosh,et al. The influence of time delay in a chaotic cancer model. , 2018, Chaos.
[17] Kathleen P Wilkie,et al. A review of mathematical models of cancer-immune interactions in the context of tumor dormancy. , 2013, Advances in experimental medicine and biology.
[18] M. D. McKay,et al. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .
[19] Davud Asemani,et al. A structural methodology for modeling immune-tumor interactions including pro- and anti-tumor factors for clinical applications. , 2018, Mathematical biosciences.
[20] D. Kirschner,et al. Modeling immunotherapy of the tumor – immune interaction , 1998, Journal of mathematical biology.
[21] G. Nicolson,et al. Direct in vitro lysis of metastatic tumor cells by cytokine-activated murine vascular endothelial cells. , 1991, Cancer research.
[22] W. Sokol,et al. Kinetics of phenol oxidation by washed cells , 1981 .
[23] Parthasakha Das,et al. Delayed Feedback Controller based Finite Time Synchronization of Discontinuous Neural Networks with Mixed Time-Varying Delays , 2018, Neural Processing Letters.
[24] Jun Tanimoto,et al. Vaccination strategies in a two-layer SIR/V-UA epidemic model with costly information and buzz effect , 2019, Commun. Nonlinear Sci. Numer. Simul..
[25] E. H. Pryde,et al. Transesterification kinetics of soybean oil 1 , 1986 .
[26] I. Cohen,et al. Modeling the influence of TH1- and TH2-type cells in autoimmune diseases. , 2000, Journal of autoimmunity.
[27] A. Perelson,et al. Nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis. , 1994, Bulletin of mathematical biology.
[28] M. Piotrowska,et al. Mathematical modelling of immune reaction against gliomas: Sensitivity analysis and influence of delays , 2013 .
[29] P. Hahnfeldt,et al. Integrated Systems and Technologies : Mathematical Oncology Tumor – Immune Dynamics Regulated in the Microenvironment Inform the Transient Nature of Immune-Induced Tumor Dormancy , 2013 .
[30] J. Tanimoto,et al. Dynamical behaviors for vaccination can suppress infectious disease – A game theoretical approach , 2019, Chaos, Solitons & Fractals.
[31] M. Karin,et al. Immunity, Inflammation, and Cancer , 2010, Cell.
[32] Sandip Banerjee,et al. Immunotherapy with Interleukin-2: A Study Based on Mathematical Modeling , 2008, Int. J. Appl. Math. Comput. Sci..
[33] E. F. Armstrong. Enzymes. By J.B.S. Haldane, M.A. Monographs on Biochemistry. Edited by R.H.A. Plimmer, D.Sc., and Sir F. G. Hopkins, M.A., M.B., D.Sc., F.R.S. Pp. vii+235. London: Longmans, Green & Co., 1930. Price 14s , 1930 .
[34] Raluca Eftimie,et al. Mathematical Models for Immunology: Current State of the Art and Future Research Directions , 2016, Bulletin of mathematical biology.
[35] Jun Tanimoto,et al. To vaccinate or not to vaccinate: A comprehensive study of vaccination-subsidizing policies with multi-agent simulations and mean-field modeling. , 2019, Journal of theoretical biology.
[36] R. Weinberg,et al. The Biology of Cancer , 2006 .