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植物生物学的生物分析资源二十年。

20 years of the Bio-Analytic Resource for Plant Biology.

作者信息

Sullivan Alexander, Lombardo Michael N, Pasha Asher, Lau Vincent, Zhuang Jian Yun, Christendat Ashley, Pereira Bruno, Zhao Tianhui, Li Youyang, Wong Rachel, Qureshi Faisal Z, Provart Nicholas J

机构信息

Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, 25 Willcocks Street, Toronto, ON M5S 3B2, Canada.

Faculty of Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa ON L1G OC5, Canada.

出版信息

Nucleic Acids Res. 2025 Jan 6;53(D1):D1576-D1586. doi: 10.1093/nar/gkae920.

DOI:10.1093/nar/gkae920
PMID:39441075
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11701662/
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 encompasses and provides visualization tools for large 'omics data sets from plants. The BAR covers data from Arabidopsis, tomato, wheat, barley and 29 other plant species (with data for 2 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 researchers via web apps. These web apps provide data analysis and visualization tools. Some of the most popular tools are eFP ('electronic fluorescent pictograph') Browsers, ePlants and ThaleMine (an Arabidopsis-specific instance of InterMine). The BAR was designated a Global Core Biodata Resource in 2023. Like other GCBRs, the BAR has excellent operational stability, provides access without login requirement, and provides an API for researchers to be able to access BAR data programmatically. We present in this update a new overarching search tool called Gaia that permits easy access to all BAR data, powered by machine learning and artificial intelligence.

摘要

植物生物学的生物分析资源库(“BAR”,网址为https://bar.utoronto.ca)将于2025年迎来其运营20周年。BAR包含来自植物的大型“组学”数据集并提供可视化工具。BAR涵盖拟南芥、番茄、小麦、大麦以及其他29种植物的数据(另外两种植物的数据即将发布)。这些数据包括核苷酸和蛋白质序列数据、基因表达数据、蛋白质-蛋白质和蛋白质-DNA相互作用、蛋白质结构、亚细胞定位以及多态性。数据存储在200多个关系数据库中,数据量达186GB,并通过网络应用程序呈现给研究人员。这些网络应用程序提供数据分析和可视化工具。一些最受欢迎的工具包括eFP(“电子荧光象形图”)浏览器、ePlants和ThaleMine(InterMine的拟南芥特定实例)。BAR在2023年被指定为全球核心生物数据资源。与其他全球核心生物数据资源一样,BAR具有出色的运营稳定性,无需登录即可访问,并为研究人员提供了一个应用程序编程接口,以便能够以编程方式访问BAR数据。在本次更新中,我们展示了一种名为盖亚的全新综合搜索工具,它借助机器学习和人工智能实现了对所有BAR数据的便捷访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/d6b6b824d7a8/gkae920fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/9fdb3932ec45/gkae920figgra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/0f57bdadd223/gkae920fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/f268c0bff6ec/gkae920fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/8b9cd65bc651/gkae920fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/d6b6b824d7a8/gkae920fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/9fdb3932ec45/gkae920figgra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/0f57bdadd223/gkae920fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/f268c0bff6ec/gkae920fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/8b9cd65bc651/gkae920fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b6c/11701662/d6b6b824d7a8/gkae920fig4.jpg

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