Reconstructing spatiotemporal gene expression data from partial observations

被引:38
作者
Cartwright, Dustin A. [1 ]
Brady, Siobhan M. [2 ,3 ,4 ,5 ]
Orlando, David A. [2 ,3 ,6 ]
Sturmfels, Bernd [1 ]
Benfey, Philip N. [2 ,3 ]
机构
[1] Univ Calif Berkeley, Dept Math, Berkeley, CA 94704 USA
[2] Duke Univ, Dept Biol, Durham, NC 27708 USA
[3] Univ Calif Berkeley, Duke Ctr Syst Biol, Berkeley, CA 94704 USA
[4] Univ Calif Davis, Genome Ctr, Davis, CA 95616 USA
[5] Univ Calif Davis, Dept Plant Biol, Davis, CA 95616 USA
[6] Duke Univ, Program Computat Biol & Bioinformat, Durham, NC USA
基金
美国国家科学基金会;
关键词
ARABIDOPSIS ROOT; MODELS; MAP;
D O I
10.1093/bioinformatics/btp437
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: 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. Results: 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.
引用
收藏
页码:2581 / 2587
页数:7
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