2009/03/24 by Dustin A. Cartwright, Dustin Cartwright, Cartwright, Dustin A. +9
Biochemistry, Genetics and Molecular Biology · #FOS: Biological sciences #Gene expression and cancer classification #Genomics (q-bio.GN) #Genomics and Phylogenetic Studies #Quantitative Methods (q-bio.QM) #Single-cell and spatial transcriptomics #q-bio.GN #q-bio.QM
paper · pdf · doi:10.48550/arxiv.0903.4027
19 pages, 4 figures
arxiv created 2009/03/24 · openalex publication_date 2009/03/24 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Developmental 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.