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RBP2GO: a comprehensive pan-species database on RNA-binding proteins, their interactions and functions
Nucleic Acids Research ( IF 14.9 ) Pub Date : 2020-11-16 , DOI: 10.1093/nar/gkaa1040
Maiwen Caudron-Herger 1 , Ralf E Jansen 1 , Elsa Wassmer 1 , Sven Diederichs 1, 2
Affiliation  

Abstract
RNA–protein complexes have emerged as central players in numerous key cellular processes with significant relevance in health and disease. To further deepen our knowledge of RNA-binding proteins (RBPs), multiple proteome-wide strategies have been developed to identify RBPs in different species leading to a large number of studies contributing experimentally identified as well as predicted RBP candidate catalogs. However, the rapid evolution of the field led to an accumulation of isolated datasets, hampering the access and comparison of their valuable content. Moreover, tools to link RBPs to cellular pathways and functions were lacking. Here, to facilitate the efficient screening of the RBP resources, we provide RBP2GO (https://RBP2GO.DKFZ.de), a comprehensive database of all currently available proteome-wide datasets for RBPs across 13 species from 53 studies including 105 datasets identifying altogether 22 552 RBP candidates. These are combined with the information on RBP interaction partners and on the related biological processes, molecular functions and cellular compartments. RBP2GO offers a user-friendly web interface with an RBP scoring system and powerful advanced search tools allowing forward and reverse searches connecting functions and RBPs to stimulate new research directions.


中文翻译:

RBP2GO:有关RNA结合蛋白,它们的相互作用和功能的综合性全物种数据库

摘要
RNA-蛋白质复合物已成为许多关键细胞过程中的核心参与者,这些过程与健康和疾病具有重大关联。为了进一步加深我们对RNA结合蛋白(RBP)的了解,已经开发了多种蛋白质组范围的策略来鉴定不同物种中的RBP,从而导致大量的研究为实验鉴定和预测的RBP候选物目录做出了贡献。但是,该领域的快速发展导致孤立数据集的积累,从而阻碍了对其有价值内容的访问和比较。此外,缺乏将RBP与细胞途径和功能联系起来的工具。在这里,为了方便有效地筛选RBP资源,我们提供了RBP2GO(https://RBP2GO.DKFZ.de),一个来自53个研究的13个物种的RBP的所有当前可用的全蛋白质组数据集的综合数据库,其中包括105个数据集,共识别22 552个RBP候选物。这些与有关RBP相互作用伙伴以及有关生物过程,分子功能和细胞区室的信息结合在一起。RBP2GO提供了一个用户友好的Web界面,其中包含RBP评分系统和强大的高级搜索工具,可通过正向和反向搜索连接功能和RBP来激发新的研究方向。
更新日期:2021-01-03
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