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dc.contributor.advisorRavasi, Timothy
dc.contributor.authorItakura, Alan
dc.date.accessioned2013-05-21T08:30:31Z
dc.date.available2014-05-31T00:00:00Z
dc.date.issued2013-05
dc.identifier.citationItakura, A. (2013). Decoupling Linear and Nonlinear Associations of Gene Expression. KAUST Research Repository. https://doi.org/10.25781/KAUST-9616Z
dc.identifier.doi10.25781/KAUST-9616Z
dc.identifier.urihttp://hdl.handle.net/10754/292462
dc.description.abstractThe FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.
dc.language.isoen
dc.subjectNonlinear associations
dc.subjectLinear associations
dc.subjectFANTOM
dc.subjectModularity
dc.titleDecoupling Linear and Nonlinear Associations of Gene Expression
dc.typeThesis
dc.contributor.departmentBiological and Environmental Science and Engineering (BESE) Division
dc.rights.embargodate2014-05-31
thesis.degree.grantorKing Abdullah University of Science and Technology
dc.contributor.committeememberGao, Xin
dc.contributor.committeememberRyu, Taewoo
thesis.degree.disciplineBioscience
thesis.degree.nameMaster of Science
dc.rights.accessrightsAt the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2014-05-31.
refterms.dateFOA2014-05-31T00:00:00Z


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