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Article: Two strategies to identify genes underlying complex diseases
Title | Two strategies to identify genes underlying complex diseases |
---|---|
Authors | |
Keywords | Complex Disease Gene Identification Microarray Obesity Proteomics |
Issue Date | 2005 |
Publisher | Bentham Science Publishers Ltd. The Journal's web site is located at http://www.bentham.org/cg/index.htm |
Citation | Current Genomics, 2005, v. 6 n. 7, p. 551-561 How to Cite? |
Abstract | Dissecting the genetic basis of complex diseases remains one of great challenges in human genetics, because these diseases have polygenic determinations and involve multiple gene-gene and gene-environmental interactions. Definite conclusions about finding genes underlying complex diseases need substantial evidence from three levels of gene function. The traditional strategy of gene identification is to determine putative susceptibility genes on the DNA level, and then to find related association between susceptibility genes and complex diseases on the RNA and protein levels. However, with rapid development of technologies of proteomics and microarrays, a new high-throughput strategy backward from protein to RNA and further to DNA becomes available for gene discovery. This strategy can systemically test gene expression, analyze co-expressed genes or regulatory network, and detect the effects of environmental factors on the onset and development of complex diseases. Here we attempt to outline these two strategies using obesity as an example of a complex disease, and to compare their advantages and disadvantages. In conclusion, we suggest that these two strategies may complement each other and thus help to uncover a more comprehensively and more completely multifaceted spectrum of genetic determination for complex diseases. © 2005 Bentham Science Publishers Ltd. |
Persistent Identifier | http://hdl.handle.net/10722/178920 |
ISSN | 2023 Impact Factor: 1.8 2023 SCImago Journal Rankings: 0.543 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lei, SF | en_US |
dc.contributor.author | Wu, S | en_US |
dc.contributor.author | Dvornyk, V | en_US |
dc.contributor.author | Deng, HW | en_US |
dc.date.accessioned | 2012-12-19T09:50:44Z | - |
dc.date.available | 2012-12-19T09:50:44Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.citation | Current Genomics, 2005, v. 6 n. 7, p. 551-561 | en_US |
dc.identifier.issn | 1389-2029 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/178920 | - |
dc.description.abstract | Dissecting the genetic basis of complex diseases remains one of great challenges in human genetics, because these diseases have polygenic determinations and involve multiple gene-gene and gene-environmental interactions. Definite conclusions about finding genes underlying complex diseases need substantial evidence from three levels of gene function. The traditional strategy of gene identification is to determine putative susceptibility genes on the DNA level, and then to find related association between susceptibility genes and complex diseases on the RNA and protein levels. However, with rapid development of technologies of proteomics and microarrays, a new high-throughput strategy backward from protein to RNA and further to DNA becomes available for gene discovery. This strategy can systemically test gene expression, analyze co-expressed genes or regulatory network, and detect the effects of environmental factors on the onset and development of complex diseases. Here we attempt to outline these two strategies using obesity as an example of a complex disease, and to compare their advantages and disadvantages. In conclusion, we suggest that these two strategies may complement each other and thus help to uncover a more comprehensively and more completely multifaceted spectrum of genetic determination for complex diseases. © 2005 Bentham Science Publishers Ltd. | en_US |
dc.language | eng | en_US |
dc.publisher | Bentham Science Publishers Ltd. The Journal's web site is located at http://www.bentham.org/cg/index.htm | en_US |
dc.relation.ispartof | Current Genomics | en_US |
dc.subject | Complex Disease | en_US |
dc.subject | Gene Identification | en_US |
dc.subject | Microarray | en_US |
dc.subject | Obesity | en_US |
dc.subject | Proteomics | en_US |
dc.title | Two strategies to identify genes underlying complex diseases | en_US |
dc.type | Article | en_US |
dc.identifier.email | Dvornyk, V: dvornyk@hku.hk | en_US |
dc.identifier.authority | Dvornyk, V=rp00693 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.2174/138920205775067710 | en_US |
dc.identifier.scopus | eid_2-s2.0-29944445973 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-29944445973&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 6 | en_US |
dc.identifier.issue | 7 | en_US |
dc.identifier.spage | 551 | en_US |
dc.identifier.epage | 561 | en_US |
dc.identifier.isi | WOS:000234101100007 | - |
dc.publisher.place | Netherlands | en_US |
dc.identifier.scopusauthorid | Lei, SF=7102453442 | en_US |
dc.identifier.scopusauthorid | Wu, S=37029336900 | en_US |
dc.identifier.scopusauthorid | Dvornyk, V=6701789786 | en_US |
dc.identifier.scopusauthorid | Deng, HW=34568563000 | en_US |
dc.identifier.citeulike | 435182 | - |
dc.identifier.issnl | 1389-2029 | - |