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dc.contributor.authorZheng, Jeffrey
dc.contributor.authorZhang, Weiqiong
dc.contributor.authorLuo, Jin
dc.contributor.authorZhou, Wei
dc.contributor.authorLiesaputra, Veronica
dc.date.accessioned2015-08-21T01:43:59Z
dc.date.available2015-08-21T01:43:59Z
dc.date.issued2014
dc.identifier.issn2153-0602
dc.identifier.urihttps://hdl.handle.net/10652/2985
dc.description.abstractVisualization Methods have played a key role in the Human Genome Project. After further development in other international projects such as ENCODE, larger numbers of Genome Databases are established and mass Genome- wide gene expression measurements are developed. In current situation, it is necessary to shift targets in computational cell biology from collecting sequential data to making higher-level interpretation and exploring efficient content-based retrieval mechanism for genomes. Mammalian genomes encode thousands of large non-coding RNAs (lncRNAs), many of which regulate gene expression, interact with chromatin regulatory complexes, and are thought to play a role in localizing these complexes to target loci across the genome. Using higher dimensional visualization tools, their complex interactive properties could be organized as different visual maps. The Variant Map Construction VMC as an emerging scheme is systematically proposed in this paper to apply multiple maps that uses four Meta symbols as same as DNA or RNA representations. System architecture of key components and core mechanism on the VMC are described. Key modules, relevant equations and their I/O parameters are discussed. Using the VMC system, two DNA data sets of multiple real sequences are tested to show their visible properties in higher levels of intrinsic relationships among relevant DNA sequences in 2D maps. Visual results are briefly analyzed to explore their intrinsic properties and symmetric characteristics on relevant genome sequences under 2D maps of the Variant Map Construction. A set of sample 2D maps are included and their characteristics are illustrated under various controllable environment.en_NZ
dc.language.isoenen_NZ
dc.publisherOMICS Groupen_NZ
dc.relation.urihttp://www.omicsonline.org/open-access/variant-map-construction-to-detect-symmetric-properties-of-genomes-on-d-distributions-2153-0602.1000150.php?aid=23904en_NZ
dc.rightsJDMGP, an open access journalen_NZ
dc.subjectsymmetric propertyen_NZ
dc.subjectgenomic sequenceen_NZ
dc.subjectpartitionen_NZ
dc.subjectsegmenten_NZ
dc.subjectmeasurementen_NZ
dc.subject2D mapsen_NZ
dc.subjectvisual distributionen_NZ
dc.subjectvariant map constructionen_NZ
dc.titleVariant Map Construction to Detect Symmetric Properties of Genomes on 2D Distributionsen_NZ
dc.typeJournal Articleen_NZ
dc.rights.holderOMICS Groupen_NZ
dc.identifier.doidoi:10.4172/2153-0602.1000150en_NZ
dc.subject.marsden0604 Geneticsen_NZ
dc.subject.marsden080109 Pattern Recognition and Data Miningen_NZ
dc.identifier.bibliographicCitationZheng, J., Zhang, W., Jin, L., Wei, Z., and Liesaputra, V. (2014). Variant Map Construction to Detect Symmetric Properties of Genomes on 2D Distributions. Journal of Data Mining in Genomics & Proteomics, 5(1)http://dx.doi.org/10.4172/2153-0602.1000150en_NZ
unitec.institutionYunnan University, Kunming Yunnan, Chinaen_NZ
unitec.institutionPeking University, Beijing, Chinaen_NZ
unitec.institutionYunnan University, Kunming Yunnan, Chinaen_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.publication.volume5(1)en_NZ
unitec.publication.titleJournal of Data Mining in Genomics & Proteomicsen_NZ
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
dc.contributor.affiliationYunan University (Kunming, China)en_NZ
dc.contributor.affiliationBeijing Universityen_NZ
unitec.identifier.roms56295en_NZ
unitec.institution.studyareaHealth Sciences


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