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Review
. 2009 Apr;21(4):1034-51.
doi: 10.1105/tpc.109.066050. Epub 2009 Apr 28.

Web-queryable large-scale data sets for hypothesis generation in plant biology

Affiliations
Review

Web-queryable large-scale data sets for hypothesis generation in plant biology

Siobhan M Brady et al. Plant Cell. 2009 Apr.

Abstract

The approaching end of the 21st century's first decade marks an exciting time for plant biology. Several National Science Foundation Arabidopsis 2010 Projects will conclude, and whether or not the stated goal of the National Science Foundation 2010 Program-to determine the function of 25,000 Arabidopsis genes by 2010-is reached, these projects and others in a similar vein, such as those performed by the AtGenExpress Consortium and various plant genome sequencing initiatives, have generated important and unprecedented large-scale data sets. While providing significant biological insights for the individual laboratories that generated them, these data sets, in conjunction with the appropriate tools, are also permitting plant biologists worldwide to gain new insights into their own biological systems of interest, often at a mouse click through a Web browser. This review provides an overview of several such genomic, epigenomic, transcriptomic, proteomic, and metabolomic data sets and describes Web-based tools for querying them in the context of hypothesis generation for plant biology. We provide five biological examples of how such tools and data sets have been used to provide biological insight.

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Figures

Figure 1.
Figure 1.
How Can Queryable Browsers Be Used to Address Biological Questions? Queryable browsers are represented in colored boxes. Left panel: How queryable browsers can be used to elucidate the function of a gene of interest. Right panel: How queryable browsers can be used to elucidate the molecular network within which a gene of interest participates.
Figure 2.
Figure 2.
Exploring Arabidopsis Gene Expression Data with the eFP Browser (Winter et al., 2007). Expression data for any one of ∼24,000 genes are “painted” onto a pictographic representation of the samples that were used to generate the RNA for expression profiling. In this view, gene expression data are from the Schmid et al. (2005) Developmental Atlas and from the Nambara lab. Here, the expression level of ABI3 (At3g24650) is seen to be highest toward the later stages of seed development, denoted by strong red coloration in the seed pictographs.

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