Mathematical Models of Tumor-Immune System Dynamics

  • Amina Eladdadi
  • Peter Kim
  • Dann Mallet
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 107)

Table of contents

  1. Front Matter
    Pages i-x
  2. Marcello Delitala, Tommaso Lorenzi, Matteo Melensi
    Pages 47-58
  3. Lisette G. de Pillis, Ami E. Radunskaya
    Pages 59-108
  4. Peter Hinow, Ami E. Radunskaya
    Pages 109-123
  5. Joanna R. Wares, Joseph J. Crivelli, Peter S. Kim
    Pages 253-275

About these proceedings

Introduction

This collection of papers offers a broad synopsis of state-of-the-art mathematical methods used in modeling the interaction between tumors and the immune system. These papers were presented at the four-day workshop on Mathematical Models of Tumor-Immune System Dynamics held in Sydney, Australia from January 7th to January 10th, 2013. The workshop brought together applied mathematicians, biologists, and clinicians actively working in the field of cancer immunology to share their current research and to increase awareness of the innovative mathematical tools that are applicable to the growing field of cancer immunology.

Recent progress in cancer immunology and advances in immunotherapy suggest that the immune system plays a fundamental role in host defense against tumors and could be utilized to prevent or cure cancer. Although theoretical and experimental studies of tumor-immune system dynamics have a long history, there are still many unanswered questions about the mechanisms that govern the interaction between the immune system and a growing tumor. The multidimensional nature of these complex interactions requires a cross-disciplinary approach to capture more realistic dynamics of the essential biology. The papers presented in this volume explore these issues and the results will be of interest to graduate students and researchers in  a variety of fields within mathematical and biological sciences.

Keywords

Agent-Based models Cancer and mathematical modeling Cancer immunology Mathematical modeling Tumor-Immune system dynamics

Editors and affiliations

  • Amina Eladdadi
    • 1
  • Peter Kim
    • 2
  • Dann Mallet
    • 3
  1. 1.Mathematics DepartmentThe College of Saint RoseAlbanyUSA
  2. 2.School of Mathematics and StatisticsUniversity of SydneySydneyAustralia
  3. 3.Mathematical Sciences SchoolQueensland University of TechnologyBrisbaneAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-1793-8
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4939-1792-1
  • Online ISBN 978-1-4939-1793-8
  • Series Print ISSN 2194-1009
  • Series Online ISSN 2194-1017
  • About this book