ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

ePlant helps biologists visualize the natural connections between DNA sequences, natural variation (polymorphisms), molecular structures, protein-protein interactions, and gene expression patterns by combining several data visualization tools with a zoomable user interface.

ePlant connects to several publicly available web services to download the latest genome, interactome, and transcriptome data for any number of genes or gene products you may be interested in. Data is displayed with a set of visualization tools that are presented with a conceptual hierarchy from big to small. Links between the different views help underscore connections between multiple levels of analysis.

Seamlessly explore data from the kilometre to nanometre scales for Arabidopsis, including natural variation data, organ and cell-type-specific gene expression patterns, subcellular localization, protein-protein interactions, and protein tertiary structures predicted for ~70% of the proteome.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on the Schmid et al. 2005 Map of Arabidopsis Development, the AtGenExpress Consortium data (Abiotic Stress - Kilian et al. 2007, Biotic Stress, and the Chemical and Hormone Series), cell-type or seed-specific data and other data.

Shown is an example output image from the eFP browser showing the expression pattern of ABI3 in the Developmental series generated by Schmid and colleagues from Detlef Weigel's group in Tübingen.

Create 'electronic fluorescent pictographic' representations of your lipid of interest based on Kehelpannala C. et al., 2021.

Create 'electronic fluorescent pictographic' representations of your gene of interest's subcellular protein product localisation based on documented and predicted subcellular localisations in Heazlewood et al.'s SUBA database.

Shown is an example output image from the Cell eFP Browser showing the subcellular localisation pattern of the gene product of At3g26520, encoding Tonoplast Intrinsic Protein 2, false coloured according to degree of support for a given location.

Create 'electronic fluorescent pictographic' representations of your gene of interest's mRNA levels in the seed coats from two wild-type and two mutant strains of Arabidopsis at 3 different developmental stages. Data are from Dean et al. 2011 (Analysis of gene expression patterns during seed coat development in Arabidopsis, in Molecular Plant). Shown is differential expression of ABI3 in different Arabidopsis seed coats.

Create 'electronic fluorescent pictographic' representations of your gene of interest's mRNA levels on polyribosomes in specific cell populations of seedlings under non-stressed and hypoxia-stressed conditions. Data are from Mustroph et al. 2009 (Profiling translatomes of discrete cell populations resolves altered cellular priorities during hypoxia in Arabidopsis). Shown is differential expression of SUS1 in different Arabidopsis tissues under hypoxia stress.

Create 'electronic fluorescent pictographic' representations of your gene of interest's salt regulated spatial-temporal expression in the Arabidopsis root. Data from Geng Y. et al. 2013 (A Spatio-Temporal Understanding of Growth Regulation during the Salt Stress Response in Arabidopsis). Shown below is differential expression of PIN3 in Arabidopsis root.

Expression Angler 2016 is a graphic user interface for our original Expression Angler. We have given the tool a complete UX makeover with the goal of making it easier to use.

This tool finds genes with similar expression patterns by calculating the correlation coefficients for all gene expression vectors as compared to an expression pattern that you define, or to an expression pattern associated with an AGI ID or gene name that you specify. The output of this tool displays an eFP image depicting the expression data and correlation coefficients for each gene that meets your cut-off criterion, or specified number of hits.

Legacy Expression Angler finds co-expressed, anti-correlated, or condition/tissue-specific genes in 5 of the data sets from the AtGenExpress Consortium, from our in-house database, or from NASCArrays. An example output image shows a selection of genes identified as co-expressed with ABI3 in the AtGenExpress Developmental Map data set from Detlef Weigel's group in Tübingen

This verson of the tool still works but we recommend using Expression Angler 2016instead.

Poplar Expression Angler finds co-expressed, anti-correlated, or condition/tissue-specific genes in two poplar data sets from the Campbell Laboratory.

Sampler Angler identifies samples exhibiting similar expression profiles, that is it will answer the question, 'which samples have the most similar expression profiles as the profile from my sample of interest?' Useful for chemical genomics or typing mutant tissues. Genes contributing the least or the most are highlighted in blue or red in the output scatterplot, shown as an example in this panel. In beta-testing, so feedback is welcome.

Perform electronic Northerns using the Expression Browser, i.e. ask how up to 125 genes of interest are being expressed, with the gene expression data sets accumulated to date in the Botany Array Resource (BAR) DB or public data sets from the AtGenExpress Consortium (Developmental - see the Schmid et al. publication, Abiotic Stress - Kilian et al. 2007, Pathogen, and Hormone Series), or others. Automatic clustering can be performed. Our databases contains more than 75 million expression measurements.

Perform electronic Northerns using the Poplar Expression Browser, i.e. ask how up to 125 genes of interest are being expressed, with the gene expression data sets accumulated to date in the Campbell Lab's PopGenExpress developmental or drought stress data sets.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data generated by Malcolm Campbell's Laboratory.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on the Benedito et al. (2008) Gene Expression Atlas of the Model Legume Medicago truncatula.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on two soybean data sets based on data from Libault et al.'s 2010 Plant Physiology and Plant Journal papers.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on Massa et al. (2011) The Transcriptome of the Reference Potato Genome Solanum tuberosum Group Phureja Clone DM1-3 415R44.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Matas et al. (2011) Tissue- and Cell-Type Specific Transcriptome Profiling of Expanding Tomato Fruit Provides Insights into Metabolic and Regulatory Specialization and Cuticle Formation.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Champigny et al. (2013) RNA-Seq effectively monitors gene expression in Eutrema salsugineum plants growing in an extreme natural habitat and in controlled growth cabinet conditions.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Camelina sativa plants. The gene expression atlas and eFP images were generated by Isobel Parkin and colleagues at Agriculture and AgriFood Canada in Saskatoon.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Arachis hypogaea plants. The gene expression atlas and eFP images were generated by Peggy Ozias-Akins and colleagues.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Fasoli et al. (2012) The Grapevine Expression Atlas Reveals a Deep Transcriptome Shift Driving the Entire Plant into a Maturation Program.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from van Bakel H et al., "The draft genome and transcriptome of Cannabis sativa.", Genome Biol, 2011 Oct 20;12(10):R102. The reads were remapped to the most recent version from Laverty KU et al., "A physical and genetic map of Cannabis sativa identifies extensive rearrangements at the THC/CBD acid synthase loci.", Genome Res, 2018 Nov 8;29(1):146-156.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from van Zhang et al., "Light-responsive expression atlas reveals the effects of light quality and intensity in Kalanchoë fedtschenkoi, a plant with crassulacean acid metabolism", GigaScience, Volume 9, Issue 3, March 2020.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Brian, L., Warren, B., McAtee, P. et al. A gene expression atlas for kiwifruit (Actinidia chinensis) and network analysis of transcription factors. BMC Plant Biol 21, 121 (2021).

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Brassica Project.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on data from Strawberry Project.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns in different parts of the maize leaf as published by Thomas Brutnell's group and others.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on two rice gene expression publications.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on two barley data sets.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on two triticale data sets normalized using RMA and MAS5.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on Brachypodium Atlas dataset.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on Wheat Atlas dataset.

BAR ThaleMine is continuation of Araport ThaleMine. ThaleMine is an instance of InterMine developed by the University of Cambridge, UK.

Search among 113 RNA-seq data sets used by Araport 11 to reannotate the Arabidopsis genome (Cheng et al. 2016, http://biorxiv.org/content/early/2016/04/05/047308). The eFP-Seq Browser will retrieve the number of reads mapped and display these above the desired Araport 11 gene model. You can sort or filter the columns.

Use this program to identify expressologs for your gene of interest in other species, that is, homologous genes that exhibit similar patterns of expressions in equivalent tissues in these other species, insofar as they exist and we've been able to identify tissue equivalencies for these species. Use the link here to directly access the Expressolog Tree Viewer, or click on the "two leaf" icon (as depicted in the thumbnail here) that appears at the top of our eFP Browser outputs to be taken to the Expressolog Tree Viewer to view expressologs for your gene of interest.

Use this program to identify over-represented n-mer 'words' in the promoter of a gene of interest, or in promoters of co-expressed genes. Words that map to PLACE are highlighted in the output listing.

A Promomer output image below shows the over-representation of the 4mer ACGT, which forms the core of the ABRE, in promoters of genes up-regulated in mesophyll cells upon ABA application, reported by Leonhardt et al. (2004).

Use Cistome to predict novel cis-elements in the promoters of co-expressed genes using several 3rd party cis-element prediction programs, or a new version of Promomer called Promomer2. Or, map on known cis-elements from PLACE. Cistome can also be used to map on PSSMs or consensus sequences onto the promoters of a defined list of AGI IDs. The output includes a sequence logo representation of the elements identified by the mapping.

A tool for finding enrichment of pairs of transcription factor binding motifs within a set of sequences.

Please click on the PMET tool on the Webtools Launcher Page

See if there are predicted (interolog) or documented interaction partners with your gene of interest. The Arabidopsis Interactions Viewer queries our database of more than 70,000 predicted interactions from Matt Geisler at SIU or 36,000 literature-documented interactions.

We also append these interactions in the output of Expression Browser and Expression Angler. Conversely, it is now possible to paint expression levels onto AIV nodes for any one of about 3500 expression data sets in the BAR. See an example of these interaction loops here.

A major overhaul of the predicted and documented Arabiodpsis protein-protein and protein-DNA interactions visualization tool, Arabidopsis Interactions Viewer (AIV). AIV2 has new updates such as faster technologies, extensive filtering options, more up-to-date interactome data, localization layouts and a cleaner user interface. Users can also choose to export their network via CSV or JSON.

NOTE: AIV2 is in beta currently, please send any feedback to Vincente[dot]lau 🌐 mail[dot]utoronto[dot]ca

See if there are predicted (interolog) or documented interaction partners with your rice gene of interest. The Rice Interactions Viewer queries our database of more than 37,000 predicted interactions from Matt Geisler at SIU or 68 literature-documented interactions from the literature.

It is also possible to paint expression levels onto RIV nodes for any one of several hundred expression data sets in the BAR.

Make long sequence logos and zoom in and out of them with Gene Slider. Use the search panel to automatically highlight motifs of interest, even when there is a high degree of wobble. Slider controls for each position of a search query make it possible to assign certainty thresholds to control whether the search function will recognize partially conserved matches. A navigation slider at the bottom of the screen indicates which region of the sequence is currently being displayed. Coloured markers along this slider indicate where query motifs have been identified, making it easy to see where multiple matches have been found.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on Physcomitrella data set.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on Selaginella dataset.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns based on the Zhang et al. (2004) Functional Landscape of Mouse Gene Expression. The thumbnail image is an example output from the Mouse eFP browser showing the expression pattern of myosin.

Create 'electronic fluorescent pictographic' representations of your gene of interest's expression patterns. The thumbnail image is an example output from the Human eFP Browser showing the expression pattern of CCR5.