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Multiscale mathematical modelling in biology and medicine

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Multiscale mathematical modelling in biology and medicine. / Chaplain, Mark A. J.

In: IMA Journal of Applied Mathematics, Vol. 76, No. 3, 06.2011, p. 371-388.

Research output: Contribution to journalArticle

Harvard

Chaplain, MAJ 2011, 'Multiscale mathematical modelling in biology and medicine' IMA Journal of Applied Mathematics, vol 76, no. 3, pp. 371-388., 10.1093/imamat/hxr025

APA

Chaplain, M. A. J. (2011). Multiscale mathematical modelling in biology and medicine. IMA Journal of Applied Mathematics, 76(3), 371-388. 10.1093/imamat/hxr025

Vancouver

Chaplain MAJ. Multiscale mathematical modelling in biology and medicine. IMA Journal of Applied Mathematics. 2011 Jun;76(3):371-388. Available from: 10.1093/imamat/hxr025

Author

Chaplain, Mark A. J. / Multiscale mathematical modelling in biology and medicine.

In: IMA Journal of Applied Mathematics, Vol. 76, No. 3, 06.2011, p. 371-388.

Research output: Contribution to journalArticle

Bibtex - Download

@article{2712339603214a16bf35a516c4c9a79e,
title = "Multiscale mathematical modelling in biology and medicine",
keywords = "Multiscale mathematical modelling, Cancer, Metastasis, Invasion, Cancer cell invasion, Tumor growth, In vitro, Adhesion, Dynamics, Systems, Tissue, Populations, Spheroids",
author = "Chaplain, {Mark A. J.}",
year = "2011",
doi = "10.1093/imamat/hxr025",
volume = "76",
number = "3",
pages = "371--388",
journal = "IMA Journal of Applied Mathematics",
issn = "0272-4960",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Multiscale mathematical modelling in biology and medicine

A1 - Chaplain,Mark A. J.

AU - Chaplain,Mark A. J.

PY - 2011/6

Y1 - 2011/6

N2 - <p>Cancer is one of the major causes of death in the world (particularly the developed world), with around 11 million people diagnosed and around 7 million people dying each year. The World Health Organization predicts that current trends show around 9 million people will die in 2015, with the number rising to 11.5 million in 2030. Cancer growth is a complicated complex phenomenon involving many interrelated processes across a wide range of spatial and temporal scales, and in spite of many advances, it is still difficult to treat and cure as the previous statistics show. New approaches are necessary if further progress in curing the disease is to be made. The description of most biological processes in the human body involves many different but interconnectedphenomena, which occur at different spatial and temporal scales. From the modelling viewpoint, there are three natural scales of interest: subcellular, cellular and tissue. The modelling described in this paper has a common theme of quantitativepredictive mathematical modelling, analysis and computational simulation of key aspects of cancer growth and treatment. The long-term goal is to build a 'virtual cancer made up of different but connected mathematical models at the different biological scales (from genes to tissue to organ)'. The development of quantitative predictive models (based on sound biological evidence and underpinned and parameterized by biological data) will no doubt have a positive impact on patients suffering from diseases such as cancer through improved clinical treatment.</p>

AB - <p>Cancer is one of the major causes of death in the world (particularly the developed world), with around 11 million people diagnosed and around 7 million people dying each year. The World Health Organization predicts that current trends show around 9 million people will die in 2015, with the number rising to 11.5 million in 2030. Cancer growth is a complicated complex phenomenon involving many interrelated processes across a wide range of spatial and temporal scales, and in spite of many advances, it is still difficult to treat and cure as the previous statistics show. New approaches are necessary if further progress in curing the disease is to be made. The description of most biological processes in the human body involves many different but interconnectedphenomena, which occur at different spatial and temporal scales. From the modelling viewpoint, there are three natural scales of interest: subcellular, cellular and tissue. The modelling described in this paper has a common theme of quantitativepredictive mathematical modelling, analysis and computational simulation of key aspects of cancer growth and treatment. The long-term goal is to build a 'virtual cancer made up of different but connected mathematical models at the different biological scales (from genes to tissue to organ)'. The development of quantitative predictive models (based on sound biological evidence and underpinned and parameterized by biological data) will no doubt have a positive impact on patients suffering from diseases such as cancer through improved clinical treatment.</p>

KW - Multiscale mathematical modelling

KW - Cancer

KW - Metastasis

KW - Invasion

KW - Cancer cell invasion

KW - Tumor growth

KW - In vitro

KW - Adhesion

KW - Dynamics

KW - Systems

KW - Tissue

KW - Populations

KW - Spheroids

U2 - 10.1093/imamat/hxr025

DO - 10.1093/imamat/hxr025

M1 - Article

JO - IMA Journal of Applied Mathematics

JF - IMA Journal of Applied Mathematics

SN - 0272-4960

IS - 3

VL - 76

SP - 371

EP - 388

ER -

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