title: Web-queryable large-scale data sets for hypothesis generation in plant biology.
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.
authors.affiliation: Section of Plant Biology and Genome Center, University of California, Davis, California 95616, USA.
authors.forename: Siobhan M
authors.initials: SM
authors.lastname: Brady
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Provart
mesh_terms: D017360:Arabidopsis / Q000235:genetics*; D019295:Computational Biology; D030541:Databases, Genetic; D044127:Epigenesis, Genetic; D020869:Gene Expression Profiling; D023281:Genomics; D020407:Internet; D040901:Proteomics; D017422:Sequence Analysis, DNA; D020539:Sequence Analysis, Protein