Comparative systems biology: from bacteria to man
Identifieur interne : 001115 ( Main/Corpus ); précédent : 001114; suivant : 001116Comparative systems biology: from bacteria to man
Auteurs : Bas Teusink ; Hans V. Westerhoff ; Frank J. BruggemanSource :
- Wiley Interdisciplinary Reviews: Systems Biology and Medicine [ 1939-5094 ] ; 2010-09.
Abstract
Comparative analyses, as carried out by comparative genomics and bioinformatics, have proven extremely powerful to obtain insight into the identity of specific genes that underlie differences and similarities across species. The central concept developed in this chapter is that important aspects of the functional differences between organisms derive not only from the differences in genetic components (which underlies comparative genomics) but also from dynamic, molecular (physical) interactions. Approaches that aim at identifying such network‐based rather than component‐based homologies between species we shall call Comparative Systems Biology. It will be illustrated by a number of examples from metabolic networks from prokaryotes, via yeast, to man. The potential for species comparisons, at the genome‐scale using classical approaches and at the more detailed level of dynamic molecular networks will be illustrated. In our opinion, comparative systems biology, as a marriage between bioinformatics and systems biology, will offer new insights into the nature of organisms for the benefit of medicine, biotechnology, and drug design. As dynamic modeling is becoming more mainstream in cell biology, the potential of comparative systems biology will become more evident. Copyright © 2010 John Wiley & Sons, Inc. For further resources related to this article, please visit the WIREs website.
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DOI: 10.1002/wsbm.74
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The central concept developed in this chapter is that important aspects of the functional differences between organisms derive not only from the differences in genetic components (which underlies comparative genomics) but also from dynamic, molecular (physical) interactions. Approaches that aim at identifying such network‐based rather than component‐based homologies between species we shall call Comparative Systems Biology. It will be illustrated by a number of examples from metabolic networks from prokaryotes, via yeast, to man. The potential for species comparisons, at the genome‐scale using classical approaches and at the more detailed level of dynamic molecular networks will be illustrated. In our opinion, comparative systems biology, as a marriage between bioinformatics and systems biology, will offer new insights into the nature of organisms for the benefit of medicine, biotechnology, and drug design. As dynamic modeling is becoming more mainstream in cell biology, the potential of comparative systems biology will become more evident. Copyright © 2010 John Wiley & Sons, Inc. For further resources related to this article, please visit the WIREs website.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Bas Teusink</name><affiliations><json:string>Systems BioInformatics, Center for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, The Netherlands</json:string><json:string>Netherlands Institute Systems Biology (NISB), The Netherlands</json:string><json:string>Kluyver Center for Genomics of Industrial Fermentation, The Netherlands</json:string></affiliations></json:item><json:item><name>Hans V. 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Approaches that aim at identifying such network‐based rather than component‐based homologies between species we shall call Comparative Systems Biology. It will be illustrated by a number of examples from metabolic networks from prokaryotes, via yeast, to man. The potential for species comparisons, at the genome‐scale using classical approaches and at the more detailed level of dynamic molecular networks will be illustrated. In our opinion, comparative systems biology, as a marriage between bioinformatics and systems biology, will offer new insights into the nature of organisms for the benefit of medicine, biotechnology, and drug design. As dynamic modeling is becoming more mainstream in cell biology, the potential of comparative systems biology will become more evident. Copyright © 2010 John Wiley & Sons, Inc. 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The central concept developed in this chapter is that important aspects of the functional differences between organisms derive not only from the differences in genetic components (which underlies comparative genomics) but also from dynamic, molecular (physical) interactions. Approaches that aim at identifying such network‐based rather than component‐based homologies between species we shall call Comparative Systems Biology. It will be illustrated by a number of examples from metabolic networks from prokaryotes, via yeast, to man. The potential for species comparisons, at the genome‐scale using classical approaches and at the more detailed level of dynamic molecular networks will be illustrated. In our opinion, comparative systems biology, as a marriage between bioinformatics and systems biology, will offer new insights into the nature of organisms for the benefit of medicine, biotechnology, and drug design. As dynamic modeling is becoming more mainstream in cell biology, the potential of comparative systems biology will become more evident. Copyright © 2010 John Wiley & Sons, Inc.</p><p>For further resources related to this article, please visit the <url href="http://wires.wiley.com/remdoi.cgi?doi=10.1002/wsbm.74">WIREs website</url>.</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Comparative systems biology: from bacteria to man</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>Comparative systems biology</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Comparative systems biology: from bacteria to man</title></titleInfo><name type="personal"><namePart type="given">Bas</namePart><namePart type="family">Teusink</namePart><affiliation>Systems BioInformatics, Center for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, The Netherlands</affiliation><affiliation>Netherlands Institute Systems Biology (NISB), The Netherlands</affiliation><affiliation>Kluyver Center for Genomics of Industrial Fermentation, The Netherlands</affiliation><description>Correspondence: Systems BioInformatics, Center for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, The Netherlands</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Hans V.</namePart><namePart type="family">Westerhoff</namePart><affiliation>Netherlands Institute Systems Biology (NISB), The Netherlands</affiliation><affiliation>Molecular Cell Physiology, VU University Amsterdam, The Netherlands</affiliation><affiliation>Manchester Centre for Integrative Systems Biology, University of Manchester, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Frank J.</namePart><namePart type="family">Bruggeman</namePart><affiliation>Systems BioInformatics, Center for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, The Netherlands</affiliation><affiliation>Regulatory Networks Group, NISB, The Netherlands</affiliation><affiliation>Life Sciences, Centre for Mathematics and Computer Science (CWI) Amsterdam, The Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="other" displayLabel="miscellaneous"></genre><originInfo><publisher>John Wiley & Sons, Inc.</publisher><place><placeTerm type="text">Hoboken, USA</placeTerm></place><dateIssued encoding="w3cdtf">2010-09</dateIssued><copyrightDate encoding="w3cdtf">2010</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">6</extent><extent unit="references">95</extent></physicalDescription><abstract lang="en">Comparative analyses, as carried out by comparative genomics and bioinformatics, have proven extremely powerful to obtain insight into the identity of specific genes that underlie differences and similarities across species. 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