Bio-Analytic Resource
The Bio-Analytic Resource at http://BAR.utoronto.ca provides user-friendly tools for exploring large
The Bio-Analytic Resource at http://BAR.utoronto.ca provides user-friendly tools for exploring large-scale data sets from plants. These data sets include gene expression, protein-protein interactions, and subcellular localization.
PlantGraph from the Mao Lab in Sweden is a new AI assistant for Arabidopsis. You can ask any complex question in natural language and will get deep, multi-hop, fully traceable answers with a claimed zero percent hallucination rate. Try it at: plantgraph.se. Send feedback to [email protected]!
The 36th International Conference on Arabidopsis Research 2026 webpage is now live and registration is open (icar2026.sg). The conference is from 22-26 June. Oral abstract submission deadline is February 22nd!
01/23/2026
The National Biology Competition is a great opportunity for high school students to demonstrate their proficiency and comprehension of biology 🐸🌿🧫- schools should register any interested students by April 14th at biocomp.utoronto.ca (the competition is on the 16th)
01/06/2025
We're happy to share our open-access Nucleic Acids Research paper describing 20 years of the Bio-Analytic Resource for Plant Biology! Check it out at
20 years of the Bio-Analytic Resource for Plant Biology Abstract. The Bio-Analytic Resource for Plant Biology (‘the BAR’, at https://bar.utoronto.ca) is celebrating its 20th year in operation in 2025. The BAR en
05/03/2024
The BAR is temporarily only available on http:// not https:// - we're running on our (slow) backup server as the power for the entire building the normally resides in is being shut off for the weekend for maintenance. Sorry for any inconvenience this may cause.
Plant will work at http://bar.utoronto.ca/eplant and the eFP Browser will work at http://bar.utoronto.ca/efp/cgi-bin/efpWeb.cgi
04/18/2024
Check out a nice barley seed development atlas from the
Lab! We collaborated to create a new view for Kovacik et al.'s (https://doi.org/10.1093/plcell/koae095) RNA-seq data in the BAR's Barley ePlant. Cheers 🍻!
12/12/2023
The Bio-Analytic Resource for Plant Biology at bar.utoronto.ca is thrilled to have been designated as a Global Core Biodata Resource by the Global Biodata Coalition, see https://globalbiodata.org/global-biodata-coalition-announces-outcome-of-2023-global-core-biodata-resource-selection-process/.
The Bio-Analytic Resource (BAR) at bar.utoronto.ca encompasses and provides visualization tools for large ‘omics data sets from plants. The BAR covers data from Arabidopsis, Medicago truncatula, rice, wheat, barley and 27 other plant species (with data for 3 others to be released soon). These data include nucleotide and protein sequence data, gene expression data, protein-protein and protein-DNA interactions, protein structures, subcellular localizations, and polymorphisms. The data are stored in more than 200 relational databases holding 186 GB of data and are presented to the user via web apps. These web apps provide data analysis and visualization tools that are hosted on the BAR. Some of the most popular tools are eFP (“electronic fluorescent pictograph”) Browsers, ePlants, and ThaleMine (an Arabidopsis-specific instance of InterMine). The BAR receives about 4M page views a month by plant researchers worldwide.
The Provart Lab, which runs the BAR, has worked collaboratively with researchers around the world to develop the 157 “electronic fluorescent pictograph” views for visualizing expression data in our collection of eFP Browsers and ePlants. The effort is substantial, so much so that we are co-authors on 43 of the 60 papers that are considered BAR publications, see https://bar.utoronto.ca/publications. These 60 BAR papers have collectively been cited 11,011 times since the BAR went online in 2003. Several international resources link to the BAR and also serve up BAR expression pictographs (“eFP images”), such as TAIR, SoyBase, and MaizeGDB. In terms of experiential learning, 79 undergraduate students – mostly from the University of Toronto – have undertaken undergraduate research projects in the Provart Lab that have supported the BAR, either through tool building, data set analysis, or algorithm development. Twenty-five of these are co-authors on BAR publications, along with a further 25 trainees from the Provart Lab.
In the past 5 years, grants from Genome Canada/Ontario Genomics (OGI-162) and NSERC (the National Science and Engineering Research Council of Canada), as well as pedagogy grants and a research stipend from the Faculty of Arts and Science at the University of Toronto to Nicholas Provart for being departmental chair, have ensured continued operation of the BAR. We also very much appreciate all the cool data sets from researchers around the world to which we have been able to facilitate access 🙌🤩!
07/13/2023
We are happy to announce the addition of 26k Alphafold2 structures to the BAR's Arabidopsis ePlant (bar.utoronto.ca/eplant). Explore structures predicted by both Alphafold2 and Phyre2, and experimentally determined ones for ~400 gene products where available from the PDB, in the context of conserved/Pfam domains and non-synonymous SNPs from the 1001 Genomes Project. Implemented by Vincent Lau, Asher Pasha, and a talented undergrad, Isaiah Hazelwood.
07/12/2023
The BAR's Asher Pasha has updated and upgraded Thalemine to version v5.1.0-20230710. This includes InterMine software v5.1.0 and data as of July 10, 2023. Check it out at bar.utoronto.ca/thalemine !
ThaleMine: Home Integrated queryable database for Arabidopsis
06/01/2023
The BAR's Nicholas Provart has just released a new course "Data Visualization for Genome Biology" on Coursera.org ...The past decade has seen a vast increase in the amount of data available to biologists, driven by the dramatic decrease in cost and concomitant rise in throughput of various next-generation sequencing technologies, such that a project unimaginable 10 years ago was recently proposed, the Earth BioGenomes Project, which aims to sequence the genomes of all eukaryotic species on the planet within the next 10 years. So while data are no longer limiting, accessing and interpreting those data has become a bottleneck. One important aspect of interpreting data is data visualization. This new course introduces theoretical topics in data visualization through mini-lectures, and applied aspects in the form of hands-on labs. The labs use both web-based tools and R, so students at all computer skill levels can benefit. Syllabus may be viewed at https://tinyurl.com/DataViz4GenomeBio. Check it out at https://www.coursera.org/learn/data-visualization-for-genome-biology/ (free to audit, or pay a small fee for a certificate). The course was developed with input from Jamie Waese, Calvin Mok, and David Guttman.
02/22/2023
From our collaborator Marek Mutwil at NTU in Singapore: Climate change is intensifying abiotic stresses that harm ecosystems and crop yields. How can we adapt? We found that Marchantia polymorpha performs arithmetic operations to respond to multiple stresses, providing insight into how plants acclimatize. https://rdcu.be/c58Qs . Work done by Tan Qiao Wen with help from Ph.D. student Lim Peng Ken. We also provide gene expression databases for Marchantia https://conekt.plant.tools and http://bar.utoronto.ca/efp_marchantia/cgi-bin/efpWeb.cgi
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