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Article: Using biomarker signature patterns for an mRNA molecular diagnostic of mouse embryonic stem cell differentiation state

TitleUsing biomarker signature patterns for an mRNA molecular diagnostic of mouse embryonic stem cell differentiation state
Authors
Issue Date2007
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/
Citation
B M C Genomics, 2007, v. 8 article no. 210 How to Cite?
AbstractBACKGROUND: The pluripotency and self-renewal capabilities, which define the 'stemness' state, of mouse embryonic stem (ES) cells, are usually investigated by functional assays or quantitative measurements of the expression levels of known ES cell markers. Strong correlations between these expression levels and functional assays, particularly at the early stage of cell differentiation, have usually not been observed. An effective molecular diagnostic to properly identify the differentiation state of mouse ES cells, prior to further experimentation, is needed. RESULTS: A novel molecular pattern recognition procedure has been developed to diagnose the differentiation state of ES cells. This is based on mRNA transcript levels of genes differentially expressed between ES cells and their differentiating progeny. Large publicly available ES cell data sets from various platforms were used to develop and test the diagnostic model. Signature patterns consisting of five gene expression levels achieved high accuracy at determining the cell state (sensitivity and specificity > 97%). CONCLUSION: The effective ES cell state diagnostic scheme described here can be implemented easily to assist researchers in identifying the differentiation state of their cultures. It also provides a step towards standardization of experiments relying on cells being in the stem cell or differentiating state.
Persistent Identifierhttp://hdl.handle.net/10722/57173
ISSN
2023 Impact Factor: 3.5
2023 SCImago Journal Rankings: 1.047
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYap, DYLen_HK
dc.contributor.authorSmith, DKen_HK
dc.contributor.authorZhang, XWen_HK
dc.contributor.authorHill, Jen_HK
dc.date.accessioned2010-04-12T01:28:15Z-
dc.date.available2010-04-12T01:28:15Z-
dc.date.issued2007en_HK
dc.identifier.citationB M C Genomics, 2007, v. 8 article no. 210en_HK
dc.identifier.issn1471-2164en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57173-
dc.description.abstractBACKGROUND: The pluripotency and self-renewal capabilities, which define the 'stemness' state, of mouse embryonic stem (ES) cells, are usually investigated by functional assays or quantitative measurements of the expression levels of known ES cell markers. Strong correlations between these expression levels and functional assays, particularly at the early stage of cell differentiation, have usually not been observed. An effective molecular diagnostic to properly identify the differentiation state of mouse ES cells, prior to further experimentation, is needed. RESULTS: A novel molecular pattern recognition procedure has been developed to diagnose the differentiation state of ES cells. This is based on mRNA transcript levels of genes differentially expressed between ES cells and their differentiating progeny. Large publicly available ES cell data sets from various platforms were used to develop and test the diagnostic model. Signature patterns consisting of five gene expression levels achieved high accuracy at determining the cell state (sensitivity and specificity > 97%). CONCLUSION: The effective ES cell state diagnostic scheme described here can be implemented easily to assist researchers in identifying the differentiation state of their cultures. It also provides a step towards standardization of experiments relying on cells being in the stem cell or differentiating state.en_HK
dc.languageengen_HK
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenomics/en_HK
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.rightsB M C Genomics. Copyright © BioMed Central Ltd.en_HK
dc.subject.meshBiological Markers - metabolismen_HK
dc.subject.meshEmbryonic Stem Cells - cytologyen_HK
dc.subject.meshGene Expression Profiling - methodsen_HK
dc.subject.meshRNA, Messenger - metabolismen_HK
dc.subject.meshTranscription Factors - metabolismen_HK
dc.titleUsing biomarker signature patterns for an mRNA molecular diagnostic of mouse embryonic stem cell differentiation stateen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1471-2164&volume=8 article no. 210&spage=&epage=&date=2007&atitle=Using+biomarker+signature+patterns+for+an+mRNA+molecular+diagnostic+of+mouse+embryonic+stem+cell+differentiation+stateen_HK
dc.identifier.emailYap, DYL: daniely@bii.a-star.edu.sgen_HK
dc.identifier.emailSmith, DK: dsmith@hkucc.hku.hken_HK
dc.identifier.emailZhang, XW: snow_dance@sina.comen_HK
dc.identifier.emailHill, J: jeffreyh@bii.a-star.edu.sgen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1186/1471-2164-8-210en_HK
dc.identifier.pmid17605829en_HK
dc.identifier.pmcidPMC1931595en_HK
dc.identifier.scopuseid_2-s2.0-34547424913-
dc.identifier.hkuros135513-
dc.identifier.isiWOS:000248311100001-
dc.identifier.citeulike1432103-
dc.identifier.issnl1471-2164-

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