FatPlants:植物脂质相关基因和代谢途径综合信息系统。

IF 3.4 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Database: The Journal of Biological Databases and Curation Pub Date : 2024-08-05 DOI:10.1093/database/baae074
Chunhui Xu, Trey Shaw, Sai Akhil Choppararu, Yiwei Lu, Shaik Naveed Farooq, Yongfang Qin, Matt Hudson, Brock Weekley, Michael Fisher, Fei He, Jose Roberto Da Silva Nascimento, Nicholas Wergeles, Trupti Joshi, Philip D Bates, Abraham J Koo, Doug K Allen, Edgar B Cahoon, Jay J Thelen, Dong Xu
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引用次数: 0

摘要

FatPlants 是一个开放存取的网络数据库,它整合了植物中脂质相关基因、蛋白质和代谢途径的数据、注释、分析结果和可视化信息。作为一种可挖掘的资源,FatPlants 提供了一个用户友好型界面,可促进对植物脂质代谢调控的研究,并支持旨在提高作物含油量的育种工作。该网络资源是利用我们自己的研究数据、公共资源和学术文献中收集到的数据开发的,包含多种植物中已知的脂肪酸相关蛋白、基因和途径的信息,重点关注最大甘氨酸、拟南芥和荠菜。此外,该平台还包括基于机器学习的方法和导航工具,旨在帮助确定代谢途径和蛋白质相互作用的特征。全面的基因和蛋白质信息卡、基本局部比对搜索工具搜索功能、来自 AphaFold 的相似结构搜索能力以及基于 ChatGPT 的蛋白质信息查询功能都是该平台的附加功能。数据库网址:https://www.fatplants.net/。
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FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants.

FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/.

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来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
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