Reconstructing Spatiotemporal Gene Expression Data from Partial Observations

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dc.creatorCartwright, Dustin A.
dc.creatorBrady, Siobhan M.
dc.creatorOrlando, David A.
dc.creatorSturmfels, Bernd
dc.creatorBenfey, Philip N.
dc.date2009-03-24
dc.date.accessioned2026-07-07T12:56:03Z
dc.date.available2026-07-07T12:56:03Z
dc.descriptionDevelopmental transcriptional networks in plants and animals operate in both space and time. To understand these transcriptional networks it is essential to obtain whole-genome expression data at high spatiotemporal resolution. Substantial amounts of spatial and temporal microarray expression data previously have been obtained for the Arabidopsis root; however, these two dimensions of data have not been integrated thoroughly. Complicating this integration is the fact that these data are heterogeneous and incomplete, with observed expression levels representing complex spatial or temporal mixtures. Given these partial observations, we present a novel method for reconstructing integrated high resolution spatiotemporal data. Our method is based on a new iterative algorithm for finding approximate roots to systems of bilinear equations.
dc.description19 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/0903.4027
dc.identifierhttp://arxiv.org/abs/0903.4027
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/224454
dc.subjectGenomics
dc.subjectQuantitative Methods
dc.titleReconstructing Spatiotemporal Gene Expression Data from Partial Observations
dc.typetext

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