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Mathematical modelling of chromosome...

Karschau, Jens.

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Mathematical modelling of chromosome replication and replicative stress

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mathematical modelling of chromosome replication and replicative stress/ by Jens Karschau.
Author:	Karschau, Jens.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xiii, 76 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Optimal Origin Placement for Minimal Replication Time -- Actively Replicating Domains Randomly Associate into Replication Factories -- Summary and Conclusions.
Contained By:	Springer eBooks
Subject:	DNA replication - Mathematical models. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-08861-7
ISBN:	9783319088617 (electronic bk.)

Mathematical modelling of chromosome replication and replicative stress
Karschau, Jens.

Mathematical modelling of chromosome replication and replicative stress[electronic resource] /by Jens Karschau. - Cham :Springer International Publishing :2015. - xiii, 76 p. :ill. (some col.), digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Optimal Origin Placement for Minimal Replication Time -- Actively Replicating Domains Randomly Associate into Replication Factories -- Summary and Conclusions.

DNA replication is arguably the most crucial process at work in living cells. It is the mechanism by which organisms pass their genetic information from one generation to the next, and life on Earth would be unthinkable without it. Despite the discovery of DNA structure in the 1950s, the mechanism of its replication remains rather elusive. This work makes important contributions to this line of research. In particular, it addresses two key questions in the area of DNA replication: which evolutionary forces drive the positioning of replication origins in the chromosome; and how is the spatial organization of replication factories achieved inside the nucleus of a cell?. A cross-disciplinary approach uniting physics and biology is at the heart of this research. Along with experimental support, statistical physics theory produces optimal origin positions and provides a model for replication fork assembly in yeast. Advances made here can potentially further our understanding of disease mechanisms such as the abnormal replication in cancer.

ISBN: 9783319088617 (electronic bk.)

Standard No.: 10.1007/978-3-319-08861-7doiSubjects--Topical Terms:

2132621
DNA replication
--Mathematical models.

LC Class. No.: QP624.5.R48

Dewey Class. No.: 572.8645

Mathematical modelling of chromosome replication and replicative stress
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245 1 0 $a Mathematical modelling of chromosome replication and replicative stress $h [electronic resource] / $c by Jens Karschau.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xiii, 76 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a Introduction -- Optimal Origin Placement for Minimal Replication Time -- Actively Replicating Domains Randomly Associate into Replication Factories -- Summary and Conclusions.
520 $a DNA replication is arguably the most crucial process at work in living cells. It is the mechanism by which organisms pass their genetic information from one generation to the next, and life on Earth would be unthinkable without it. Despite the discovery of DNA structure in the 1950s, the mechanism of its replication remains rather elusive. This work makes important contributions to this line of research. In particular, it addresses two key questions in the area of DNA replication: which evolutionary forces drive the positioning of replication origins in the chromosome; and how is the spatial organization of replication factories achieved inside the nucleus of a cell?. A cross-disciplinary approach uniting physics and biology is at the heart of this research. Along with experimental support, statistical physics theory produces optimal origin positions and provides a model for replication fork assembly in yeast. Advances made here can potentially further our understanding of disease mechanisms such as the abnormal replication in cancer.
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