Review and application of group theory to molecular systems biology

<p>Abstract</p> <p>In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this paper we br...

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Main Authors: Rietman Edward A, Karp Robert L, Tuszynski Jack A
Format: Article
Language:English
Published: BMC 2011-06-01
Series:Theoretical Biology and Medical Modelling
Online Access:http://www.tbiomed.com/content/8/1/21
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spelling doaj-372652b6af504b118720c791927c1dce2020-11-25T02:18:28ZengBMCTheoretical Biology and Medical Modelling1742-46822011-06-01812110.1186/1742-4682-8-21Review and application of group theory to molecular systems biologyRietman Edward AKarp Robert LTuszynski Jack A<p>Abstract</p> <p>In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this paper we briefly describe possible open problems. In connection with the genetic code we propose that it may be possible to use perturbation theory to explore the adjacent possibilities in the 64-dimensional space-time manifold of the evolving genome.</p> <p>With regards to algebraic graph theory, there are several minor open problems we discuss. In relation to network dynamics and groupoid formalism we suggest that the network graph might not be the main focus for understanding the phenotype but rather the phase space of the network dynamics. We show a simple case of a <it>C</it><sub>6 </sub>network and its phase space network. We envision that the molecular network of a cell is actually a complex network of hypercycles and feedback circuits that could be better represented in a higher-dimensional space. We conjecture that targeting nodes in the molecular network that have key roles in the phase space, as revealed by analysis of the automorphism decomposition, might be a better way to drug discovery and treatment of cancer.</p> http://www.tbiomed.com/content/8/1/21
collection DOAJ
language English
format Article
sources DOAJ
author Rietman Edward A
Karp Robert L
Tuszynski Jack A
spellingShingle Rietman Edward A
Karp Robert L
Tuszynski Jack A
Review and application of group theory to molecular systems biology
Theoretical Biology and Medical Modelling
author_facet Rietman Edward A
Karp Robert L
Tuszynski Jack A
author_sort Rietman Edward A
title Review and application of group theory to molecular systems biology
title_short Review and application of group theory to molecular systems biology
title_full Review and application of group theory to molecular systems biology
title_fullStr Review and application of group theory to molecular systems biology
title_full_unstemmed Review and application of group theory to molecular systems biology
title_sort review and application of group theory to molecular systems biology
publisher BMC
series Theoretical Biology and Medical Modelling
issn 1742-4682
publishDate 2011-06-01
description <p>Abstract</p> <p>In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this paper we briefly describe possible open problems. In connection with the genetic code we propose that it may be possible to use perturbation theory to explore the adjacent possibilities in the 64-dimensional space-time manifold of the evolving genome.</p> <p>With regards to algebraic graph theory, there are several minor open problems we discuss. In relation to network dynamics and groupoid formalism we suggest that the network graph might not be the main focus for understanding the phenotype but rather the phase space of the network dynamics. We show a simple case of a <it>C</it><sub>6 </sub>network and its phase space network. We envision that the molecular network of a cell is actually a complex network of hypercycles and feedback circuits that could be better represented in a higher-dimensional space. We conjecture that targeting nodes in the molecular network that have key roles in the phase space, as revealed by analysis of the automorphism decomposition, might be a better way to drug discovery and treatment of cancer.</p>
url http://www.tbiomed.com/content/8/1/21
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