Dr Peter Kim

F07 - Carslaw Building
The University of Sydney

Telephone 9351 2970
Fax 9351 4534

Website Personal web page
Curriculum vitae Curriculum vitae

Research interests

I work in mathematical biology, a rapidly growing interdisciplinary field that requires a synthesis of information from a variety of perspectives, creative modelling, and interaction with researchers from a range of areas.

Specific areas that I work on include mathematical immunology, cancer dynamics, virus dynamics, mosquito-borne infections, and human evolution. To address these problems, I apply ordinary, delay, and partial differential equations and agent/individual-based models.

I am a member of the Applied Mathematics Research Group.

Teaching and supervision

Supervision

Postdoc

  • Danya Rose (Jun 2016-present)
  • Matthew Chan (Mar 2016-present)

PhD

  • Anthony Cheung (Jul 2016-present)
  • Adrianne Jenner (Aug 2015-present)
  • Sara Loo (Mar 2015-present)
  • Matthew Chan (Aug 2012-Feb 2016)
  • James Reoch (U of Adelaide, external supervisor, Jul 2015-Aug 2016)
  • David Khoury (UNSW, associate supervisor, Feb 2012-2016)

Masters

  • Collin Zheng (2016)
  • Jared Field (2015)

Honours

  • Hak Joon Kim (2016)
  • Adarsh Kumbhari (2016)
  • Pantea Pooladvand (2015-2016)
  • Adrianne Jenner (Jul 2014-Jun 2015)
  • Jared Field (2014)
  • Sara Loo (U of Wollongong, associate supervisor, 2014)
  • Andrea Cooper (2013)
  • James Reoch (2012)

Undergraduate - 1st to 3rd year

  • Vaishnavi Calisa (Talented Student Program 2nd year project, 2016)
  • Vaishnavi Calisa and Benjamin Xie (Talented Student Program 1st year project, 2015)
  • Noah Johnston, Mona Khosh, Kelsey Mckinnon, Justin Phu, and Stephanie Sun (Talented Student Program 1st year project, with 3rd-yr mentor Edward Burrowes, 2015)
  • Jian Cao (3rd-yr vacation scholar, 2013)
  • Edward Kim (3rd-yr vacation scholar, 2012)

Timetable

Current research students

Project title Research student
A Mathematical Investigation into the Large Game Hunting Behaviours of Hunter Gatherer Populations Sara LOO

Current projects

If you are interested in pursuing a PhD or collaboration along the lines of one of these projects or a related area, please feel free to contact me at (pkim@maths.usyd.edu.au).

Evolution of human post-menopausal longevity: Grandmother Hypothesis

A big, outstanding question in human evolution is why humans developed such long lifespans, greatly exceeding the end of female fertility. As far as we know, only pilot whales and killer whales share this trait. The Grandmother Hypothesis proposes that humans developed increased longevity as ancestral grandmothers began to help care for their daughters' children, allowing their daughters to move on to the next child sooner. As part of an exciting collaboration with a leading anthropologist at the University of Utah, Salt Lake City, USA, we develop models of primate populations to determine under what conditions grandmother help could drive increased longevity without increased reproduction. We also consider alternative hypotheses, including the Hunting Hypothesis that male hunting in groups and long-term pair bonding with females pushed human longevity.

The podcast of a Public Lecture by Prof. Kristen Hawkes on "Grandmothers and Human Evolution" on 15 Aug 2015 as part of the Sydney Science Festival is available here.

Guardian Angels - social network modelling (In collaboration with A/Prof. Simon Poon of the School of Information Technologies)

The Guardian Angel concept proposes the idea that a decentralised social support network in a connected community can more effectively motivate individuals to improve health and lifestyle habits than a centralised system of a few localised hubs, e.g., health care professionals, monitoring a large number of spokes, e.g., patients. For example, suppose there is a cohort of patients who are individually cared by one doctor, so all interactions are impersonal and brief. The Guardian Angel idea is to organise patients, so that each individual has one or more guardian angels from among other patients and is assigned to be a guardian angel for one or more other people. The angel has the ability to view the other person's activities, such health records and accomplishments of health goals, and then encourage and motivate the person to continue on a positive trajectory. Every person tries to motivate someone and is motivated by someone else so that the health and lifestyle of the whole community improves. The question is how the dynamics of the system are dependent on features such as the size of the cohort, structure of the social network, randomness of events, and variation between individuals. The project would involve simulating possible Guardian Angel systems using differential equations or agent-based models.

Cancer vaccines and immunotherapy

Immunotherapy is a new and promising approach to cancer treatment. It involves helping the body's immune defences defeat tumours. Several methods involve T cell vaccination, dendritic cell vaccination, and cytokine therapy. In collaboration with a cancer immunologist at the City of Hope and Beckman Research Institute, Los Angeles, USA, we develop mathematical models to describe interactions between immune cells and tumour cells with and without treatment to help understand data and propose new strategies for investigation.

Cancer virotherapy

Cancer virotherapy is newly emerging strategy that involves infecting patients with genetically-engineered viruses to attack tumours. It is closely related to cancer immunotherapy, because viruses can often be engineered to induce a concurrent anti-tumour immune response or combined with other immunotherapies. In collaboration with a genetic engineering laboratory at Hanyang University, Seoul, Korea, we develop models of viral infection of tumour masses and the possible recruitment of a simultaneous immune response.

International links

Korea South

(Hanyang University, Seoul) Collaboration with the Gene Therapy Laboratory.

United States

(City of Hope and Beckman Research Institute, Los Angeles, California) Collaboration with the Faculty of Cancer Immunotherapeutics and Tumor Immunology.

United States

(University of Utah, Salt Lake City, Utah) Collaboration with the Departments of Mathematics, Biology, and Anthropology.

Selected grants

2016

  • Human longevity: Modelling social changes that propelled its evolution; Kim P, Hawkes K; Australian Research Council (ARC)/Discovery Projects (DP).

2015

  • Mathematical Modelling of Human Life History Eveolution; Kim P; DVC Research/Bridging Support Grant.

2012

  • Mathematical modelling of breast cancer immunity: Guiding the development of preventative breast cancer vaccines; Kim P; Australian Research Council (ARC)/Discovery Early Career Researcher Award (DECRA).

Selected publications

Download citations: PDF RTF Endnote

Book Chapters

  • Cooper, A., Kim, P. (2014). A Cellular Automata and a Partial Differential Equation Model of Tumor-Immune Dynamics and Chemotaxis. In Amina Eladdadi, Peter Kim, Dann Mallet (Eds.), Mathematical Models of Tumor-Immune System Dynamics, (pp. 21-46). New York: Springer Science+Business Media.
  • Wares, J., Crivelli, J., Kim, P. (2014). Differential Equation Techniques for Modeling a Cycle-Specific Oncolytic Virotherapeutic. In Amina Eladdadi, Peter Kim, Dann Mallet (Eds.), Mathematical Models of Tumor-Immune System Dynamics, (pp. 253-275). New York: Springer Science+Business Media.
  • Kim, P., Lee, P., Levy, D. (2013). Basic Principles in Modeling Adaptive Regulation and Immunodominance. In Urszula Ledzewicz, Heinz Schattler, Avner Friedman and Eugene Kashdan (Eds.), Mathematical Methods and Models in Biomedicine, (pp. 33-57). New York: Springer.
  • Kim, P., Levy, D., Lee, P. (2009). Modeling and Simulation of the Immune System as a Self-Regulating Network. In Michael L Johnson and Ludwig Brand (Eds.), Methods in Enzymology: Volume 467 Computer Methods, Part B, (pp. 79-109). London: Academic Press.
  • Kim, P., Lee, P., Levy, D. (2007). Mini-Transplants for Chronic Myelogenous Leukemia: A Modeling Perspective. In Isabelle Queinnec, Sophie Tarbouriech, Germain Garcia and Silviu-Iulian Niculesc (Eds.), Biology and Control Theory: Current Challenges, (pp. 3-20). Germany: Springer.

Journals

  • Koop, J., Kim, P., Knutie, S., Adler, F., Clayton, D. (2016). An introduced parasitic fly may lead to local extinction of Darwin’s finch populations. Journal of Applied Ecology, 53(2), 511-518. [More Information]
  • Chan, M., Hawkes, K., Kim, P. (2016). Evolution of longevity, age at last birth and sexual conflict with grandmothering. Journal of Theoretical Biology, 393, 145-157. [More Information]
  • Coxworth, J., Kim, P., McQueen, J., Hawkes, K. (2015). Grandmothering life histories and human pair bonding. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 112(38), 11806-11811. [More Information]
  • Chan, M., Shine, R., Brown, G., Kim, P. (2015). Mathematical modelling of spatial sorting and evolution in a host-parasite system. Journal of Theoretical Biology, 380, 530-541. [More Information]
  • Kim, P., Crivelli, J., Choi, I., Yun, C., Wares, J. (2015). Quantitative impact of immunomodulation versus oncolysis with cytokine-expressing virus therapeutics. Mathematical Biosciences and Engineering (MBE), 12(4), 841-858. [More Information]
  • Wares, J., Crivelli, J., Yun, C., Choi, I., Gevertz, J., Kim, P. (2015). Treatment strategies for combining immunostimulatory oncolytic virus therapeutics with dendritic cell injections. Mathematical Biosciences and Engineering (MBE), 12(6), 1237-1256. [More Information]
  • Frascoli, F., Kim, P., Hughes, B., Landman, K. (2014). A dynamical model of tumour immunotherapy. Mathematical Biosciences, 253, 50-62. [More Information]
  • Chan, M., Kim, P. (2014). An Age-Structured Approach to Modelling Behavioural Variation Maintained by Life-History Trade-Offs. PloS One, 9(1), 1-10. [More Information]
  • Khoury, D., Cromer, D., Best, S., James, K., Kim, P., Engwerda, C., Haque, A., Davenport, M. (2014). Effect of Mature Blood-Stage Plasmodium Parasite Sequestration on Pathogen Biomass in Mathematical and In Vivo Models of Malaria. Infection and Immunity, 82(1), 212-220. [More Information]
  • Kim, P., McQueen, J., Coxworth, J., Hawkes, K. (2014). Grandmothering drives the evolution of longevity in a probabilistic model. Journal of Theoretical Biology, 353(July), 84-94. [More Information]
  • Chan, M., Kim, P. (2014). Modelling the Impact of Marine Reserves on a Population with Depensatory Dynamics. Bulletin of Mathematical Biology, 76, 2122-2143. [More Information]
  • Chan, M., Kim, P. (2014). Modelling the Impact of Marine Reserves on a Population with Depensatory Dynamics. Bulletin of Mathematical Biology, 76(9), 2122-2143. [More Information]
  • Chan, M., Kim, P. (2013). Modelling a Wolbachia Invasion Using a Slow-Fast Dispersal Reaction-Diffusion Approach. Bulletin of Mathematical Biology, 75(9), 1501-1523. [More Information]
  • Adler, F., Kim, P. (2013). Models of contrasting strategies of rhinovirus immune manipulation. Journal of Theoretical Biology, 327(21), 1-10. [More Information]
  • Crivelli, J., Foldes, J., Kim, P., Wares, J. (2012). A mathematical model for cell cycle-specific cancer virotherapy. Journal of Biological Dynamics, 6(Supp. 1), 104-120. [More Information]
  • Kim, P., Coxworth, J., Hawkes, K. (2012). Increased longevity evolves from grandmothering. Proceedings of the Royal Society B, 279(1749), 4880-4884. [More Information]
  • Kim, P., Lee, P. (2012). Modeling Protective Anti-Tumor Immunity via Preventative Cancer Vaccines Using a Hybrid Agentbased and Delay Differential Equation Approach. PLoS Computational Biology, 8(10), 1-16. [More Information]
  • Hawkes, K., Kim, P., Kennedy, B., Bohlender, R., Hawks, J. (2011). A reappraisal of grandmothering and natural selection. Proceedings of the Royal Society B, 278(1714), 1936-1938. [More Information]
  • Kim, P., Lee, P., Levy, D. (2011). A Theory of Immunodominance and Adaptive Regulation. Bulletin of Mathematical Biology, 73(7), 1645-1665. [More Information]
  • Mazenc, F., Kim, P., Niculescu, S. (2011). Stability of an imatinib and immune model with delays. IMA journal of mathematical control and information, 28(4), 447-462. [More Information]
  • Paquin, D., Kim, P., Lee, P., Levy, D. (2011). Strategic Treatment Interruptions During Imatinib Treatment of Chronic Myelogenous Leukemia. Bulletin of Mathematical Biology, 73(5), 1082-1100. [More Information]
  • Kim, P., Lee, P. (2011). T cell state transition produces an emergent change detector. Journal of Theoretical Biology, 275(1), 59-69. [More Information]
  • Kim, P., Lee, P., Levy, D. (2010). Emergent Group Dynamics Governed by Regulatory Cells Produce a Robust Primary T Cell Response. Bulletin of Mathematical Biology, 72(3), 611-644. [More Information]
  • Doumic-Jauffret, M., Kim, P., Perthame, B. (2010). Stability Analysis of a Simplified Yet Complete Model for Chronic Myelogenous Leukemia. Bulletin of Mathematical Biology, 72(7), 1732-1759. [More Information]
  • Niculescu, S., Kim, P., Gu, K., Lee, P., Levy, D. (2010). Stability crossing boundaries of delay systems modeling immune dynamics in Leukemia. Discrete and Continuous Dynamical Systems - Series B, 13(1), 129-156. [More Information]
  • Peet, M., Kim, P., Niculescu, S., Levy, D. (2009). New computational tools for modeling chronic myelogenous leukemia. Mathematical Modelling of Natural Phenomena, 4(2), 119-139. [More Information]
  • Kim, P., Lee, P., Levy, D. (2008). A PDE Model for Imatinib-Treated Chronic Myelogenous Leukemia. Bulletin of Mathematical Biology, 70, 1994-2016. [More Information]
  • Kim, P., Lee, P., Levy, D. (2008). Dynamics and Potential Impact of the Immune Response to Chronic Myelogenous Leukemia. PLoS Computational Biology, 4(6), e1000095-17 pages. [More Information]
  • Kim, P., Lee, P., Levy, D. (2008). Modeling Imatinib-Treated Chronic Myelogenous Leukemia: Reducing the Complexity of Agent-Based Models. Bulletin of Mathematical Biology, 70(3), 728-744. [More Information]
  • Kim, P., Lee, P., Levy, D. (2007). Modeling regulation mechanisms in the immune system. Journal of Theoretical Biology, 246(1), 33-69. [More Information]
  • DeConde, R., Kim, P., Levy, D., Lee, P. (2005). Post-transplantation dynamics of the immune response to chronic myelogenous. Journal of Theoretical Biology, 236(1), 39-59.

Conferences

  • Sweatman, W., Mercer, G., Boland, J., Cusimano, N., Greenwood, A., Harley, K., van Heijster, P., Kim, P., Maisano, J., Nelson, M., et al (2016). Seaweed cultivation and the remediation of by-products from ethanol production: a glorious green growth. 2014 Mathematics and Statistics in Industry Study Group (MISG 2014), Brisbane: Australian Mathematical Society. [More Information]
  • Eladdadi, A., Kim, P., Mallet, D. (2014). Mathematical Models of Tumor-Immune System Dynamics. Springer Proceedings in Mathematics and Statistics, New York: Springer.
  • Peet, M., Kim, P., Lee, P. (2012). Biological Circuit Models of the Immune Regulatory Response: a Decentralized Control System. 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), New York, USA: (IEEE) Institute of Electrical and Electronics Engineers. [More Information]
  • Kim, P. (2011). Modeling Leukemia stem cell differentiation: Bridging agent-based and partial differential equation models. Advanced computer and information technologies, Yekaterinburg, Russia: Ural Federal University.
  • Mazenc, F., Kim, P., Niculescu, S. (2008). Stability of a Gleevec and immune model with delays. 47th IEEE Conference on Decision and Control CDC 2008, Piscataway: (IEEE) Institute of Electrical and Electronics Engineers. [More Information]
  • Niculescu, S., Kim, P., Lee, P., Levy, D. (2007). On stability of a combined Gleevec and immune model in chronic leukemia: Exploiting delay system structure. 7th IFAC Symposium on Nonlinear Control Systems, Pretoria, South Africa: International Federation of Automatic Control (IFAC). [More Information]
  • Niculescu, S., Kim, P., Gu, D., Levy, D. (2006). On the stability crossing boundaries of some delay systems modeling immune dynamics of leukemia. 17th International Symposium on Mathematical Theory of Networks and Systems, Japan: MTNS.

2016

  • Koop, J., Kim, P., Knutie, S., Adler, F., Clayton, D. (2016). An introduced parasitic fly may lead to local extinction of Darwin’s finch populations. Journal of Applied Ecology, 53(2), 511-518. [More Information]
  • Chan, M., Hawkes, K., Kim, P. (2016). Evolution of longevity, age at last birth and sexual conflict with grandmothering. Journal of Theoretical Biology, 393, 145-157. [More Information]
  • Sweatman, W., Mercer, G., Boland, J., Cusimano, N., Greenwood, A., Harley, K., van Heijster, P., Kim, P., Maisano, J., Nelson, M., et al (2016). Seaweed cultivation and the remediation of by-products from ethanol production: a glorious green growth. 2014 Mathematics and Statistics in Industry Study Group (MISG 2014), Brisbane: Australian Mathematical Society. [More Information]

2015

  • Coxworth, J., Kim, P., McQueen, J., Hawkes, K. (2015). Grandmothering life histories and human pair bonding. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 112(38), 11806-11811. [More Information]
  • Chan, M., Shine, R., Brown, G., Kim, P. (2015). Mathematical modelling of spatial sorting and evolution in a host-parasite system. Journal of Theoretical Biology, 380, 530-541. [More Information]
  • Kim, P., Crivelli, J., Choi, I., Yun, C., Wares, J. (2015). Quantitative impact of immunomodulation versus oncolysis with cytokine-expressing virus therapeutics. Mathematical Biosciences and Engineering (MBE), 12(4), 841-858. [More Information]
  • Wares, J., Crivelli, J., Yun, C., Choi, I., Gevertz, J., Kim, P. (2015). Treatment strategies for combining immunostimulatory oncolytic virus therapeutics with dendritic cell injections. Mathematical Biosciences and Engineering (MBE), 12(6), 1237-1256. [More Information]

2014

  • Cooper, A., Kim, P. (2014). A Cellular Automata and a Partial Differential Equation Model of Tumor-Immune Dynamics and Chemotaxis. In Amina Eladdadi, Peter Kim, Dann Mallet (Eds.), Mathematical Models of Tumor-Immune System Dynamics, (pp. 21-46). New York: Springer Science+Business Media.
  • Frascoli, F., Kim, P., Hughes, B., Landman, K. (2014). A dynamical model of tumour immunotherapy. Mathematical Biosciences, 253, 50-62. [More Information]
  • Chan, M., Kim, P. (2014). An Age-Structured Approach to Modelling Behavioural Variation Maintained by Life-History Trade-Offs. PloS One, 9(1), 1-10. [More Information]
  • Wares, J., Crivelli, J., Kim, P. (2014). Differential Equation Techniques for Modeling a Cycle-Specific Oncolytic Virotherapeutic. In Amina Eladdadi, Peter Kim, Dann Mallet (Eds.), Mathematical Models of Tumor-Immune System Dynamics, (pp. 253-275). New York: Springer Science+Business Media.
  • Khoury, D., Cromer, D., Best, S., James, K., Kim, P., Engwerda, C., Haque, A., Davenport, M. (2014). Effect of Mature Blood-Stage Plasmodium Parasite Sequestration on Pathogen Biomass in Mathematical and In Vivo Models of Malaria. Infection and Immunity, 82(1), 212-220. [More Information]
  • Kim, P., McQueen, J., Coxworth, J., Hawkes, K. (2014). Grandmothering drives the evolution of longevity in a probabilistic model. Journal of Theoretical Biology, 353(July), 84-94. [More Information]
  • Eladdadi, A., Kim, P., Mallet, D. (2014). Mathematical Models of Tumor-Immune System Dynamics. Springer Proceedings in Mathematics and Statistics, New York: Springer.
  • Chan, M., Kim, P. (2014). Modelling the Impact of Marine Reserves on a Population with Depensatory Dynamics. Bulletin of Mathematical Biology, 76, 2122-2143. [More Information]
  • Chan, M., Kim, P. (2014). Modelling the Impact of Marine Reserves on a Population with Depensatory Dynamics. Bulletin of Mathematical Biology, 76(9), 2122-2143. [More Information]

2013

  • Kim, P., Lee, P., Levy, D. (2013). Basic Principles in Modeling Adaptive Regulation and Immunodominance. In Urszula Ledzewicz, Heinz Schattler, Avner Friedman and Eugene Kashdan (Eds.), Mathematical Methods and Models in Biomedicine, (pp. 33-57). New York: Springer.
  • Chan, M., Kim, P. (2013). Modelling a Wolbachia Invasion Using a Slow-Fast Dispersal Reaction-Diffusion Approach. Bulletin of Mathematical Biology, 75(9), 1501-1523. [More Information]
  • Adler, F., Kim, P. (2013). Models of contrasting strategies of rhinovirus immune manipulation. Journal of Theoretical Biology, 327(21), 1-10. [More Information]

2012

  • Crivelli, J., Foldes, J., Kim, P., Wares, J. (2012). A mathematical model for cell cycle-specific cancer virotherapy. Journal of Biological Dynamics, 6(Supp. 1), 104-120. [More Information]
  • Peet, M., Kim, P., Lee, P. (2012). Biological Circuit Models of the Immune Regulatory Response: a Decentralized Control System. 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), New York, USA: (IEEE) Institute of Electrical and Electronics Engineers. [More Information]
  • Kim, P., Coxworth, J., Hawkes, K. (2012). Increased longevity evolves from grandmothering. Proceedings of the Royal Society B, 279(1749), 4880-4884. [More Information]
  • Kim, P., Lee, P. (2012). Modeling Protective Anti-Tumor Immunity via Preventative Cancer Vaccines Using a Hybrid Agentbased and Delay Differential Equation Approach. PLoS Computational Biology, 8(10), 1-16. [More Information]

2011

  • Hawkes, K., Kim, P., Kennedy, B., Bohlender, R., Hawks, J. (2011). A reappraisal of grandmothering and natural selection. Proceedings of the Royal Society B, 278(1714), 1936-1938. [More Information]
  • Kim, P., Lee, P., Levy, D. (2011). A Theory of Immunodominance and Adaptive Regulation. Bulletin of Mathematical Biology, 73(7), 1645-1665. [More Information]
  • Kim, P. (2011). Modeling Leukemia stem cell differentiation: Bridging agent-based and partial differential equation models. Advanced computer and information technologies, Yekaterinburg, Russia: Ural Federal University.
  • Mazenc, F., Kim, P., Niculescu, S. (2011). Stability of an imatinib and immune model with delays. IMA journal of mathematical control and information, 28(4), 447-462. [More Information]
  • Paquin, D., Kim, P., Lee, P., Levy, D. (2011). Strategic Treatment Interruptions During Imatinib Treatment of Chronic Myelogenous Leukemia. Bulletin of Mathematical Biology, 73(5), 1082-1100. [More Information]
  • Kim, P., Lee, P. (2011). T cell state transition produces an emergent change detector. Journal of Theoretical Biology, 275(1), 59-69. [More Information]

2010

  • Kim, P., Lee, P., Levy, D. (2010). Emergent Group Dynamics Governed by Regulatory Cells Produce a Robust Primary T Cell Response. Bulletin of Mathematical Biology, 72(3), 611-644. [More Information]
  • Doumic-Jauffret, M., Kim, P., Perthame, B. (2010). Stability Analysis of a Simplified Yet Complete Model for Chronic Myelogenous Leukemia. Bulletin of Mathematical Biology, 72(7), 1732-1759. [More Information]
  • Niculescu, S., Kim, P., Gu, K., Lee, P., Levy, D. (2010). Stability crossing boundaries of delay systems modeling immune dynamics in Leukemia. Discrete and Continuous Dynamical Systems - Series B, 13(1), 129-156. [More Information]

2009

  • Kim, P., Levy, D., Lee, P. (2009). Modeling and Simulation of the Immune System as a Self-Regulating Network. In Michael L Johnson and Ludwig Brand (Eds.), Methods in Enzymology: Volume 467 Computer Methods, Part B, (pp. 79-109). London: Academic Press.
  • Peet, M., Kim, P., Niculescu, S., Levy, D. (2009). New computational tools for modeling chronic myelogenous leukemia. Mathematical Modelling of Natural Phenomena, 4(2), 119-139. [More Information]

2008

  • Kim, P., Lee, P., Levy, D. (2008). A PDE Model for Imatinib-Treated Chronic Myelogenous Leukemia. Bulletin of Mathematical Biology, 70, 1994-2016. [More Information]
  • Kim, P., Lee, P., Levy, D. (2008). Dynamics and Potential Impact of the Immune Response to Chronic Myelogenous Leukemia. PLoS Computational Biology, 4(6), e1000095-17 pages. [More Information]
  • Kim, P., Lee, P., Levy, D. (2008). Modeling Imatinib-Treated Chronic Myelogenous Leukemia: Reducing the Complexity of Agent-Based Models. Bulletin of Mathematical Biology, 70(3), 728-744. [More Information]
  • Mazenc, F., Kim, P., Niculescu, S. (2008). Stability of a Gleevec and immune model with delays. 47th IEEE Conference on Decision and Control CDC 2008, Piscataway: (IEEE) Institute of Electrical and Electronics Engineers. [More Information]

2007

  • Kim, P., Lee, P., Levy, D. (2007). Mini-Transplants for Chronic Myelogenous Leukemia: A Modeling Perspective. In Isabelle Queinnec, Sophie Tarbouriech, Germain Garcia and Silviu-Iulian Niculesc (Eds.), Biology and Control Theory: Current Challenges, (pp. 3-20). Germany: Springer.
  • Kim, P., Lee, P., Levy, D. (2007). Modeling regulation mechanisms in the immune system. Journal of Theoretical Biology, 246(1), 33-69. [More Information]
  • Niculescu, S., Kim, P., Lee, P., Levy, D. (2007). On stability of a combined Gleevec and immune model in chronic leukemia: Exploiting delay system structure. 7th IFAC Symposium on Nonlinear Control Systems, Pretoria, South Africa: International Federation of Automatic Control (IFAC). [More Information]

2006

  • Niculescu, S., Kim, P., Gu, D., Levy, D. (2006). On the stability crossing boundaries of some delay systems modeling immune dynamics of leukemia. 17th International Symposium on Mathematical Theory of Networks and Systems, Japan: MTNS.

2005

  • DeConde, R., Kim, P., Levy, D., Lee, P. (2005). Post-transplantation dynamics of the immune response to chronic myelogenous. Journal of Theoretical Biology, 236(1), 39-59.

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