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dc.contributor.authorSigurdsson, MI
dc.contributor.authorJamshidi, N
dc.contributor.authorJonsson, JJ
dc.contributor.authorPalsson, BO
dc.date.accessioned2009-03-05T11:09:54Z
dc.date.available2009-03-05T11:09:54Z
dc.date.issued2009-01-01
dc.date.submitted2009-03-05
dc.identifier.citationEpigenetics. 2009, 4(1):43-46en
dc.identifier.issn1559-2294
dc.identifier.pmid19218833
dc.identifier.urihttp://hdl.handle.net/2336/52273
dc.descriptionTo access publisher full text version of this article. Please click on the hyperlink in Additional Links fielden
dc.description.abstractSystem analysis of metabolic network reconstructions can be used to calculate functional states or phenotypes. This provides tools to study the metabolic effects of genetic and epigenetic properties, such as dosage sensitivity. We used the genome-scale reconstruction of human metabolism (Recon 1) to analyze the effect of nine known or predicted imprinted genes on metabolic phenotypes. Simulations of maternal deletion of ATP10A indicated an anabolic metabolism consistent with the known clinical phenotypes of obesity. The abnormal expression of the other genes affected fewer subsections of metabolism consistent with a lack of established clinical phenotypes. We found that four of nine genes had metabolic effect as predicted by the Haig's parental conflict theory.
dc.languageENG
dc.language.isoisen
dc.publisherLandes Bioscienceen
dc.relation.urlhttp://www.landesbioscience.com/journals/epigenetics/article/7603en
dc.subject.meshPubMed - in processen
dc.titleGenome-scale network analysis of imprinted human metabolic genes.is
dc.typeArticleen
dc.identifier.eissn1559-2308
dc.contributor.departmentDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Iceland, Reykjavik, Iceland; Center for Systems Biology, University of Iceland, Reykjavik, Iceland; Department of Genetics and Molecular Medicine, Landspitali-University Hospital, San Diego, La Jolla, California, USA.en
dc.identifier.journalEpigenetics : official journal of the DNA Methylation Societyen
html.description.abstractSystem analysis of metabolic network reconstructions can be used to calculate functional states or phenotypes. This provides tools to study the metabolic effects of genetic and epigenetic properties, such as dosage sensitivity. We used the genome-scale reconstruction of human metabolism (Recon 1) to analyze the effect of nine known or predicted imprinted genes on metabolic phenotypes. Simulations of maternal deletion of ATP10A indicated an anabolic metabolism consistent with the known clinical phenotypes of obesity. The abnormal expression of the other genes affected fewer subsections of metabolism consistent with a lack of established clinical phenotypes. We found that four of nine genes had metabolic effect as predicted by the Haig's parental conflict theory.


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