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A coexpression database for plant species, which provides a parallel view of multiple coexpression data sets with network analysis tools. The user can effectively find functional gene relationships and design experiments to confirm the gene functions by reverse genetics and general molecular biological techniques. ATTED-II includes new and updated coexpression data and analysis tools. ATTED-II version 8.0 now includes eight microarray- and six RNAseq-based coexpression data sets for nine species (Arabidopsis, field mustard, soybean, barrel medick, poplar, tomato, grape, rice and maize). Importantly, five species (Arabidopsis, soybean, tomato, rice and maize) are now supported by both microarray- and RNAseq-based coexpression data.


Contains information about co-expressions. COEXPEDIA gathers co-expressions from individual studies associated with medical subject headings (MeSH) and calculated from a statistical test for co-functionality. The database aims to improve identification of unknown gene-to-disease, gene-to-drug, disease-to-disease, and disease-to-drug associations by using MeSH-associated co-expressions. It includes about 8 million co-expressions from 384 and 248 Gene Expression Omnibus (GEO) series for humans and mice respectively.


An accurate and high-resolution atlas of gene expression and gene co-regulation in human retina. We collected 50 high-quality post-mortem human retinas from donors and performed high-coverage RNA-sequencing analysis to yield a comprehensive RefT of the human retina. Moreover, we exploited inter-individual variability in gene expression to infer a gene co-expression network and to predict, via a guilty-by-association approach, photoreceptor-specific expression of 253 genes. This atlas represents a valuable resource for the research community at large and help in better elucidating pathophysiological processes in the human retina.

ALCOdb / Algae Gene Coexpression database

Provides microalgal gene coexpression information with a user-friendly interface. ALCOdb currently supports two model algae: the green alga Chlamydomonas reinhardtii and the red alga Cyanidioschyzon merolae. Users can retrieve coexpression information for genes of interest through three unique data pages: (i) coexpressed gene list; (ii) gene information; and (iii) coexpressed gene network. The database contains several unique characteristics for enabling interspecies comparisons, network analyses and a combined approach with differential expression analyses. ALCOdb facilitates microalgal research at the molecular level and promote the evolutionary understanding of cellular systems from microalgae to higher plants.


A cell-specific database that contains information about gene co-expression in immune cells, identifying co-expression and correlation between any two genes. The strength of co-expression of queried genes is indicated by signal values and detection calls, whereas expression correlation and strength are reflected by Pearson correlation coefficients. A scatter plot of the signal values is provided to directly illustrate the extent of co-expression and correlation. In addition, the database allows the analysis of cell-specific gene expression profile across multiple experimental conditions and can generate a list of genes that are highly correlated with the queried genes.

TENOR / Transcriptome ENcyclopedia Of Rice

A database that encompasses large-scale mRNA sequencing (mRNA-seq) data obtained from rice under a wide variety of conditions. We used mRNA-seq and performed a time-course transcriptome analysis of rice, Oryza sativa L. (cv. Nipponbare), under 10 abiotic stress conditions (high salinity; high and low phosphate; high, low and extremely low cadmium; drought; osmotic; cold; and flood) and two plant hormone treatment conditions (ABA and jasmonic acid). A large number of genes that were responsive to abiotic stresses and plant hormones were detected by differential expression analysis. TENOR provides rice transcriptome data, such as transcript structures and expression profiles, as well as co-expression data and information about cis-regulatory elements in 1 kb upstream regions for each gene.

PODC / Plant Omics Data Center

A web repository for NGS transcriptomes and gene expression networks (GENs) with an interactive network viewer. Compared with existing GEN databases, the content depth of NGS mRNA-Seq data in our PODC seems without equal. In addition, we are taking advantage of the state-of-the-art natural language processing technique for cost-effective accumulation of manually curated plant annotations. These multiple enrichments of data content make PODC unique and invaluable in the plant sciences.

KAGIANA / Kazusa Arabidopsis Gene Information And Network Analysis

Allows retrieval of summary information about Arabidopsis genes. KAGIANA summarizes various Arabidopsis omics analyses from databases and tools and provides links to pages for genes of interest in databases. The database also provides ‘Tools’ macro programs including ‘Confeito’, ‘GX bar chart’, ‘GO pie chart’ and ‘ATTED chart’. It aims to assist plant biologists in accessing information from omics analyses so that they can incorporate it into their plant biology research.

RNA-seq networks

Provides aggregate networks generated with information derived from “Affymetrix Human Genome U133 Plus 2.0 Array” microarray platform. RNA-seq networks is composed of two downloadable files in R format. The first: RNA-Seq aggregates network numbers 30,705 nodes compiled from 50 individual co-expression networks and 1,970 samples. The second: microarray aggregates network, consists of a gathering of 43 individual co-expression networks, 20,283 nodes and 5,134 samples.


A database resource that collects and utilizes gene expression profiles derived from microarray platforms under various conditions to infer metabolic pathways for plants. EXPath was developed to not only comprehensively congregate the public microarray expression data from over 1000 samples in biotic stress, abiotic stress, and hormone secretion but also allow the usage of this abundant resource for coexpression analysis and differentially expression genes (DEGs) identification, finally inferring the enriched KEGG pathways and gene ontology (GO) terms of three model plants: Arabidopsis thaliana, Oryza sativa, and Zea mays. Users can access the gene expression patterns of interest under various conditions via five main functions (Gene Search, Pathway Search, DEGs Search, Pathways/GO Enrichment, and Coexpression analysis) in EXPath, which are presented by a user-friendly interface and valuable for further research.

PAN / PlantArrayNet

Provides co-expression information between genes in terms of correlation coefficients from accumulated microarray data. Given the correlation of a gene pair, the degrees of closeness between gene expression profiling are calculated and are visualized in a relational tree and a relational network. In addition, PAN supports scatter plots of log ratios between genes and links them to pathway maps, while providing a common cis-element list of promoter regions that are involved.

ViBrism / Virtual Brain with 3D-ISM

Offers a comprehensive spatial overview of gene expression patterns of the mouse brain. ViBrism provides more than 36,000 expression maps of the adult mouse brain and 45,000 expression maps of each in the developmental stages. The platform hosts a software that allows integrated analysis of 3D gene expression maps and graphs of co-expression networks. It enables the analysis of co-expression gene networks throughout the brain, along with an anatomical overview.

CSB.DB / Comprehensive Systems-Biology DataBase

Presents the results of bio-statistical analyses on gene expression data in association with additional biochemical and physiological knowledge. The main aim of CSB.DB is to provide tools that support insight into life's complexity pyramid with a special focus on the integration of data from transcript and metabolite profiling experiments. CSB.DB gives easy access to the results of large-scale co-response analyses, which are currently based exclusively on the publicly available compendia of transcript profiles. By scanning for the best co-responses among changing transcript levels, CSB.DB allows to infer hypotheses on the functional interaction of genes.

CGCDB / CHO Gene Coexpression Database

Aims to provide access to gene coexpression patterns derived from the microarray analysis of transcript expression during industrial cell culture of CHO. Users can access correlations between pairs of genes and between genes and CHO cell growth rate and cell specific productivity. It is hoped that this resource will allow researchers to prioritize cell line engineering and/or biomarker candidates to enhance CHO-based cell culture for the production of biotherapeutics.

VTCdb / ViTis Co-expression DataBase

Offers an online platform for transcriptional regulatory inference in the cultivated grapevine. VTCdb provides users to query gene(s), modules or biological processes of interests in several ways. Querying a gene(s) gives a ranked list of co-expressed genes, functional annotations and its associated module. Alternatively, browsing of modules of interests retrieves hierarchical optimized Gene Ontology enrichment and tissue/condition specificity genes within the module along with interactive network visualisation and analysis via CytoscapeWeb.

PLANEX / PLAnt co-EXpression database

An internet-based database for plant gene analysis. PLANEX contains publicly available GeneChip data obtained from the Gene Expression Omnibus (GEO) of the National Center for Biotechnology Information (NCBI). PLANEX is a genome-wide co-expression database, which allows for the functional identification of genes from a wide variety of experimental designs. It can be used for the characterization of genes for functional identification and analysis of a gene's dependency among other genes. Gene co-expression databases have been developed for other species, but gene co-expression information for plants is currently limited.

RAN / RiceArrayNet

Provides information on co-expressed genes in rice, based on two-dye microarray data. RAN is a resource that gathers information on co-expression between genes in terms of correlation coefficients (r values). The database reveals the co-expressed gene characteristics of the gene family and can also be used in the comparison of gene expression between rice and Arabidopsis. It is designed to be flexible in terms of choosing query genes and finding co-expressed genes.