Toward large-scale modeling of the microbial cell for computer simulation
In the post-genomic era, the large-scale, systematic, and functional analysis of all cellular components using transcriptomics, proteomics, and metabolomics, together with bioinformatics for the analysis of the massive amount of data generated by these “omics” methods are the focus of intensive rese...
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Veröffentlicht in: | Journal of biotechnology 2004-09, Vol.113 (1), p.281-294 |
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creator | Ishii, Nobuyoshi Robert, Martin Nakayama, Yoichi Kanai, Akio Tomita, Masaru |
description | In the post-genomic era, the large-scale, systematic, and functional analysis of all cellular components using transcriptomics, proteomics, and metabolomics, together with bioinformatics for the analysis of the massive amount of data generated by these “omics” methods are the focus of intensive research activities. As a consequence of these developments, systems biology, whose goal is to comprehend the organism as a complex system arising from interactions between its multiple elements, becomes a more tangible objective. Mathematical modeling of microorganisms and subsequent computer simulations are effective tools for systems biology, which will lead to a better understanding of the microbial cell and will have immense ramifications for biological, medical, environmental sciences, and the pharmaceutical industry.
In this review, we describe various types of mathematical models (structured, unstructured, static, dynamic, etc.), of microorganisms that have been in use for a while, and others that are emerging. Several biochemical/cellular simulation platforms to manipulate such models are summarized and the E-Cell system
1
1
The E-Cell software environment described in this article is freely available at
http://ecell.sourceforge.net/.
developed in our laboratory is introduced. Finally, our strategy for building a “whole cell metabolism model”, including the experimental approach, is presented. |
doi_str_mv | 10.1016/j.jbiotec.2004.04.038 |
format | Article |
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In this review, we describe various types of mathematical models (structured, unstructured, static, dynamic, etc.), of microorganisms that have been in use for a while, and others that are emerging. Several biochemical/cellular simulation platforms to manipulate such models are summarized and the E-Cell system
1
1
The E-Cell software environment described in this article is freely available at
http://ecell.sourceforge.net/.
developed in our laboratory is introduced. Finally, our strategy for building a “whole cell metabolism model”, including the experimental approach, is presented.</description><identifier>ISSN: 0168-1656</identifier><identifier>EISSN: 1873-4863</identifier><identifier>DOI: 10.1016/j.jbiotec.2004.04.038</identifier><identifier>PMID: 15380661</identifier><identifier>CODEN: JBITD4</identifier><language>eng</language><publisher>Lausanne: Elsevier B.V</publisher><subject>Bioinformatics ; Biological and medical sciences ; Biotechnology ; Biotechnology - methods ; Computational Biology - methods ; Computer Simulation ; Escherichia coli - physiology ; Fundamental and applied biological sciences. Psychology ; Mathematical model ; Metabolic engineering ; Metabolome ; Models, Biological ; Systems biology</subject><ispartof>Journal of biotechnology, 2004-09, Vol.113 (1), p.281-294</ispartof><rights>2004 Elsevier B.V.</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c525t-f86ecbd3a397b6860eba2d4be48a691ccd8a8c9a2f8e2b70f86dcae1b6e00bd53</citedby><cites>FETCH-LOGICAL-c525t-f86ecbd3a397b6860eba2d4be48a691ccd8a8c9a2f8e2b70f86dcae1b6e00bd53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0168165604003190$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>309,310,314,776,780,785,786,3537,23909,23910,25118,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16147813$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15380661$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ishii, Nobuyoshi</creatorcontrib><creatorcontrib>Robert, Martin</creatorcontrib><creatorcontrib>Nakayama, Yoichi</creatorcontrib><creatorcontrib>Kanai, Akio</creatorcontrib><creatorcontrib>Tomita, Masaru</creatorcontrib><title>Toward large-scale modeling of the microbial cell for computer simulation</title><title>Journal of biotechnology</title><addtitle>J Biotechnol</addtitle><description>In the post-genomic era, the large-scale, systematic, and functional analysis of all cellular components using transcriptomics, proteomics, and metabolomics, together with bioinformatics for the analysis of the massive amount of data generated by these “omics” methods are the focus of intensive research activities. As a consequence of these developments, systems biology, whose goal is to comprehend the organism as a complex system arising from interactions between its multiple elements, becomes a more tangible objective. Mathematical modeling of microorganisms and subsequent computer simulations are effective tools for systems biology, which will lead to a better understanding of the microbial cell and will have immense ramifications for biological, medical, environmental sciences, and the pharmaceutical industry.
In this review, we describe various types of mathematical models (structured, unstructured, static, dynamic, etc.), of microorganisms that have been in use for a while, and others that are emerging. Several biochemical/cellular simulation platforms to manipulate such models are summarized and the E-Cell system
1
1
The E-Cell software environment described in this article is freely available at
http://ecell.sourceforge.net/.
developed in our laboratory is introduced. Finally, our strategy for building a “whole cell metabolism model”, including the experimental approach, is presented.</description><subject>Bioinformatics</subject><subject>Biological and medical sciences</subject><subject>Biotechnology</subject><subject>Biotechnology - methods</subject><subject>Computational Biology - methods</subject><subject>Computer Simulation</subject><subject>Escherichia coli - physiology</subject><subject>Fundamental and applied biological sciences. 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As a consequence of these developments, systems biology, whose goal is to comprehend the organism as a complex system arising from interactions between its multiple elements, becomes a more tangible objective. Mathematical modeling of microorganisms and subsequent computer simulations are effective tools for systems biology, which will lead to a better understanding of the microbial cell and will have immense ramifications for biological, medical, environmental sciences, and the pharmaceutical industry.
In this review, we describe various types of mathematical models (structured, unstructured, static, dynamic, etc.), of microorganisms that have been in use for a while, and others that are emerging. Several biochemical/cellular simulation platforms to manipulate such models are summarized and the E-Cell system
1
1
The E-Cell software environment described in this article is freely available at
http://ecell.sourceforge.net/.
developed in our laboratory is introduced. Finally, our strategy for building a “whole cell metabolism model”, including the experimental approach, is presented.</abstract><cop>Lausanne</cop><cop>Amsterdam</cop><cop>New York, NY</cop><pub>Elsevier B.V</pub><pmid>15380661</pmid><doi>10.1016/j.jbiotec.2004.04.038</doi><tpages>14</tpages></addata></record> |
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subjects | Bioinformatics Biological and medical sciences Biotechnology Biotechnology - methods Computational Biology - methods Computer Simulation Escherichia coli - physiology Fundamental and applied biological sciences. Psychology Mathematical model Metabolic engineering Metabolome Models, Biological Systems biology |
title | Toward large-scale modeling of the microbial cell for computer simulation |
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