D1194–D1201 Nucleic Acids Research, 2012, Vol. 40, Database issue doi:10.1093/nar/gkr938 Published online 13 November 2011 PLEXdb: gene expression resources for plants and plant pathogens Sudhansu Dash1,2,3, John Van Hemert1,2,4, Lu Hong 4 , Roger P. Wise4,5,6 and Julie A. Dickerson1,3,4,* 1Virtual Reality Application Center, 2Crop Genome Informatics Lab, 3Electrical and Computer Engineering, 4Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA, 5Crop and Insect Genetics, Genomics, and Informatics Research, USDA-ARS and 6Plant Pathology and Microbiology, Iowa State University, Ames, IA 50011, USA Received August 15, 2011; Revised October 9, 2011; Accepted October 11, 2011 ABSTRACT PLEXdb (http://www.plexdb.org), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facilitate the interpretation of structure, function and regulation of genes in economically im- portant plants. A list of Gene Atlas experiments highlights data sets that give responses across dif- ferent developmental stages, conditions and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI) tool supports mapping gene lists onto corresponding genes from model plant organisms, including rice and Arabidopsis. MGI predicts homologies, displays gene structures and supporting information for annotated genes and full-length cDNAs. The gene list-processing wizard guides users through PLEXdb functions for creating, analyzing, annotating and managing gene lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher level analyses, such as ANOVA and clustering. PLEXdb also provides methods for users to track how gene expression changes across many different experiments using the Gene OscilloScope. This tool can identify interesting expression patterns, such as up-regulation under diverse con- ditions or checking any gene’s suitability as a steady-state control. INTRODUCTION PLEXdb (Plant Expression Database) is a gene expression-based resource to bridge between genotype to phenotype through transcript proﬁling. PLEXdb inte- grates multiple data sets from a wide variety of plant and plant pathogen microarrays and provides a single site to access, analyze and disseminate expression data for comprehensive comparative functional genomics studies (1,2). The goal of PLEXdb is to make this data easily accessible to help users answer biological questions and begin to leverage existing results from related large-scale expression studies. The primary goal of the PLEXdb resource is to provide integration of data and tools that are currently accessible only from disparate resources. Without this integration, researchers, students and teachers would have to download expression data from a repository site; check for conformity to standards that would allow cross-experiment comparisons; map the respective array (or RNA-Seq tags) to genes and those genes to genomic locations and orthologs in other species; install local software for expression data analysis; rely on disparate resources to view associated data and develop their own methods to post-process results, (e.g. obtain additional sequence data for upload into promoter motif-ﬁnding software). Thus, PLEXdb facilitates these many different tasks using a single web interface that is easily accessible to any researcher within two or three clicks from the PLEXdb front page (See Fig. 1). PLEXdb is complementary and synergistic to other expression data archives such as NCBI-GEO and ArrayExpress. General repositories, such as the Gene Expression Omnibus (GEO) (3) and ArrayExpress (4), act as central data distribution hubs for species ranging from E. coli to humans. General repositories make the *To whom correspondence should be addressed. Tel: +515 294 7705; Fax: +515 294 8432; Email: julied@iastate.edu The Author(s) 2011. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.