Dynamic epigenetic mode analysis using spatial temporal clustering
Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for charact...
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| Veröffentlicht in: | BMC bioinformatics 2016-12, Vol.17 (Suppl 17), p.537-537, Article 537 |
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| container_issue | Suppl 17 |
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| container_title | BMC bioinformatics |
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| creator | Gan, YangLan Tao, Han Zou, Guobing Yan, Cairong Guan, Jihong |
| description | Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for characterizing fundamental properties of epigenomic dynamics and revealing regulatory roles of epigenetic modifications.
This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns.
The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process. |
| doi_str_mv | 10.1186/s12859-016-1331-z |
| format | Article |
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This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns.
The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process.</description><identifier>ISSN: 1471-2105</identifier><identifier>EISSN: 1471-2105</identifier><identifier>DOI: 10.1186/s12859-016-1331-z</identifier><identifier>PMID: 28155634</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Analysis ; Cell differentiation ; Cell Differentiation - genetics ; Cluster Analysis ; DNA Methylation ; Embryonic stem cells ; Embryonic Stem Cells - metabolism ; Embryonic Stem Cells - physiology ; Epigenesis, Genetic ; Epigenetic inheritance ; Gene Expression Regulation, Developmental ; Genetic aspects ; Histones - metabolism ; Humans ; Physiological aspects</subject><ispartof>BMC bioinformatics, 2016-12, Vol.17 (Suppl 17), p.537-537, Article 537</ispartof><rights>COPYRIGHT 2016 BioMed Central Ltd.</rights><rights>The Author(s) 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c500t-9483772b0bac42a333fd1b37b868517b072394d502c85bba2c19c23a3501c3ae3</citedby><cites>FETCH-LOGICAL-c500t-9483772b0bac42a333fd1b37b868517b072394d502c85bba2c19c23a3501c3ae3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5259871/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5259871/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28155634$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gan, YangLan</creatorcontrib><creatorcontrib>Tao, Han</creatorcontrib><creatorcontrib>Zou, Guobing</creatorcontrib><creatorcontrib>Yan, Cairong</creatorcontrib><creatorcontrib>Guan, Jihong</creatorcontrib><title>Dynamic epigenetic mode analysis using spatial temporal clustering</title><title>BMC bioinformatics</title><addtitle>BMC Bioinformatics</addtitle><description>Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for characterizing fundamental properties of epigenomic dynamics and revealing regulatory roles of epigenetic modifications.
This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns.
The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process.</description><subject>Analysis</subject><subject>Cell differentiation</subject><subject>Cell Differentiation - genetics</subject><subject>Cluster Analysis</subject><subject>DNA Methylation</subject><subject>Embryonic stem cells</subject><subject>Embryonic Stem Cells - metabolism</subject><subject>Embryonic Stem Cells - physiology</subject><subject>Epigenesis, Genetic</subject><subject>Epigenetic inheritance</subject><subject>Gene Expression Regulation, Developmental</subject><subject>Genetic aspects</subject><subject>Histones - metabolism</subject><subject>Humans</subject><subject>Physiological aspects</subject><issn>1471-2105</issn><issn>1471-2105</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNptkUtr3TAQhUVpaR7tD-imGLppFk40kmXJm0KSvgKBQB9rIctjV8WWXEsuvfn10eWmIReCFho03zmM5hDyBugpgKrPIjAlmpJCXQLnUN4-I4dQSSgZUPH8UX1AjmL8TSlIRcVLcsAUCFHz6pBcfNx4Mzlb4OwG9JhyOYUOC-PNuIkuFmt0fijibJIzY5FwmsOSCzuuMeGSe6_Ii96MEV_f38fk5-dPPy6_ltc3X64uz69LKyhNZVMpLiVraWtsxQznvO-g5bJVtRIgWyoZb6pOUGaVaFvDLDSWccMFBcsN8mPyYec7r-2EnUWf8iB6Xtxklo0Oxun9jne_9BD-asFEoyRkg_f3Bkv4s2JMenLR4jgaj2GNOq9UCMZYxTP6bocOZkTtfB-yo93i-rySlZI1pU2mTp-g8ukwrzR47F1-3xOc7Akyk_BfGswao776_m2fhR1rlxDjgv3DT4Hqbfx6F7_O8ett_Po2a94-XtGD4n_e_A5eJKnV</recordid><startdate>20161223</startdate><enddate>20161223</enddate><creator>Gan, YangLan</creator><creator>Tao, Han</creator><creator>Zou, Guobing</creator><creator>Yan, Cairong</creator><creator>Guan, Jihong</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20161223</creationdate><title>Dynamic epigenetic mode analysis using spatial temporal clustering</title><author>Gan, YangLan ; Tao, Han ; Zou, Guobing ; Yan, Cairong ; Guan, Jihong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c500t-9483772b0bac42a333fd1b37b868517b072394d502c85bba2c19c23a3501c3ae3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Analysis</topic><topic>Cell differentiation</topic><topic>Cell Differentiation - genetics</topic><topic>Cluster Analysis</topic><topic>DNA Methylation</topic><topic>Embryonic stem cells</topic><topic>Embryonic Stem Cells - metabolism</topic><topic>Embryonic Stem Cells - physiology</topic><topic>Epigenesis, Genetic</topic><topic>Epigenetic inheritance</topic><topic>Gene Expression Regulation, Developmental</topic><topic>Genetic aspects</topic><topic>Histones - metabolism</topic><topic>Humans</topic><topic>Physiological aspects</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gan, YangLan</creatorcontrib><creatorcontrib>Tao, Han</creatorcontrib><creatorcontrib>Zou, Guobing</creatorcontrib><creatorcontrib>Yan, Cairong</creatorcontrib><creatorcontrib>Guan, Jihong</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BMC bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gan, YangLan</au><au>Tao, Han</au><au>Zou, Guobing</au><au>Yan, Cairong</au><au>Guan, Jihong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic epigenetic mode analysis using spatial temporal clustering</atitle><jtitle>BMC bioinformatics</jtitle><addtitle>BMC Bioinformatics</addtitle><date>2016-12-23</date><risdate>2016</risdate><volume>17</volume><issue>Suppl 17</issue><spage>537</spage><epage>537</epage><pages>537-537</pages><artnum>537</artnum><issn>1471-2105</issn><eissn>1471-2105</eissn><abstract>Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for characterizing fundamental properties of epigenomic dynamics and revealing regulatory roles of epigenetic modifications.
This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns.
The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>28155634</pmid><doi>10.1186/s12859-016-1331-z</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; SpringerLink Journals - AutoHoldings; PubMed Central Open Access; Springer Nature OA Free Journals |
| subjects | Analysis Cell differentiation Cell Differentiation - genetics Cluster Analysis DNA Methylation Embryonic stem cells Embryonic Stem Cells - metabolism Embryonic Stem Cells - physiology Epigenesis, Genetic Epigenetic inheritance Gene Expression Regulation, Developmental Genetic aspects Histones - metabolism Humans Physiological aspects |
| title | Dynamic epigenetic mode analysis using spatial temporal clustering |
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