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Branching process models of cancer

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Branching process models of cancer

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Branching process models of cancer/ by Richard Durrett.
Author:	Durrett, Richard.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	vii, 63 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Cancer - Mathematical models. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-16065-8
ISBN:	9783319160658 (electronic bk.)

Branching process models of cancer
Durrett, Richard.

Branching process models of cancer[electronic resource] /by Richard Durrett. - Cham :Springer International Publishing :2015. - vii, 63 p. :ill., digital ;24 cm. - Mathematical biosciences institute lecture series ;v.1. - Mathematical biosciences institute lecture series ;v.1..

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.

ISBN: 9783319160658 (electronic bk.)

Standard No.: 10.1007/978-3-319-16065-8doiSubjects--Topical Terms:

848591
Cancer
--Mathematical models.

LC Class. No.: RC267

Dewey Class. No.: 616.9940015118

Branching process models of cancer
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245 1 0 $a Branching process models of cancer $h [electronic resource] / $c by Richard Durrett.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a vii, 63 p. : $b ill., digital ; $c 24 cm.
490 1 $a Mathematical biosciences institute lecture series ; $v v.1
520 $a 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.
650 0 $a Cancer $x Mathematical models. $3 848591
650 0 $a Branching processes. $3 646787
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650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
650 2 4 $a Mathematical and Computational Biology. $3 1566274
650 2 4 $a Cancer Research. $3 891172
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