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Branching Process Models of Cancer

  • RichardĀ Durrett

Part of the Mathematical Biosciences Institute Lecture Series book series (MBILS, volume 1.1)

Also part of the Stochastics in Biological Systems book sub series (STOCHBS, volume 1.1)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Richard Durrett
    Pages 1-63

About this book

Introduction

This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As a consequence, the authors calculate the probability that mutations that confer resistance to treatment are present at detection and quantify the extent of tumor heterogeneity. As applications, the authors evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis. These notes should be accessible to students who are familiar with Poisson processes and continuous time. Richard Durrett is mathematics professor at Duke University, USA. He is the author of 8 books, over 200 journal articles, and has supervised more than 40 Ph.D.

students. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer.

Keywords

Branching Processes Continuous Time Gamma Function Multistage theory of cancer Tumor modelling

Authors and affiliations

  • RichardĀ Durrett
    • 1
  1. 1.Duke University Department of MathematicsDurhamUSA

Bibliographic information

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