Bio-Analytic Resource

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)

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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 🙌🤩!

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.

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

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.