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A data integration approach for cell cycle analysis oriented to model simulation in systems biology

BACKGROUND: The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to m...

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Autores principales: Alfieri, Roberta, Merelli, Ivan, Mosca, Ettore, Milanesi, Luciano
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1995223/
https://www.ncbi.nlm.nih.gov/pubmed/17678529
http://dx.doi.org/10.1186/1752-0509-1-35
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author Alfieri, Roberta
Merelli, Ivan
Mosca, Ettore
Milanesi, Luciano
author_facet Alfieri, Roberta
Merelli, Ivan
Mosca, Ettore
Milanesi, Luciano
author_sort Alfieri, Roberta
collection PubMed
description BACKGROUND: The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. DESCRIPTION: In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. CONCLUSION: This integrated system is freely available in order to support systems biology research on the cell cycle and it aims to become a useful resource for collecting all the information related to actual and future models of this network. The flexibility of the database allows the addition of mathematical data which are used for simulating the behavior of the cell cycle components in the different models. The resource deals with two relevant problems in systems biology: data integration and mathematical simulation of a crucial biological process related to cancer, such as the cell cycle. In this way the resource is useful both to retrieve information about cell cycle model components and to analyze their dynamical properties. The Cell Cycle Database can be used to find system-level properties, such as stable steady states and oscillations, by coupling structure and dynamical information about models.
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spelling pubmed-19952232007-09-29 A data integration approach for cell cycle analysis oriented to model simulation in systems biology Alfieri, Roberta Merelli, Ivan Mosca, Ettore Milanesi, Luciano BMC Syst Biol Database BACKGROUND: The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. DESCRIPTION: In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. CONCLUSION: This integrated system is freely available in order to support systems biology research on the cell cycle and it aims to become a useful resource for collecting all the information related to actual and future models of this network. The flexibility of the database allows the addition of mathematical data which are used for simulating the behavior of the cell cycle components in the different models. The resource deals with two relevant problems in systems biology: data integration and mathematical simulation of a crucial biological process related to cancer, such as the cell cycle. In this way the resource is useful both to retrieve information about cell cycle model components and to analyze their dynamical properties. The Cell Cycle Database can be used to find system-level properties, such as stable steady states and oscillations, by coupling structure and dynamical information about models. BioMed Central 2007-08-01 /pmc/articles/PMC1995223/ /pubmed/17678529 http://dx.doi.org/10.1186/1752-0509-1-35 Text en Copyright © 2007 Alfieri et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database
Alfieri, Roberta
Merelli, Ivan
Mosca, Ettore
Milanesi, Luciano
A data integration approach for cell cycle analysis oriented to model simulation in systems biology
title A data integration approach for cell cycle analysis oriented to model simulation in systems biology
title_full A data integration approach for cell cycle analysis oriented to model simulation in systems biology
title_fullStr A data integration approach for cell cycle analysis oriented to model simulation in systems biology
title_full_unstemmed A data integration approach for cell cycle analysis oriented to model simulation in systems biology
title_short A data integration approach for cell cycle analysis oriented to model simulation in systems biology
title_sort data integration approach for cell cycle analysis oriented to model simulation in systems biology
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1995223/
https://www.ncbi.nlm.nih.gov/pubmed/17678529
http://dx.doi.org/10.1186/1752-0509-1-35
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