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Babel's tower revisited: a universal resource for cross-referencing across annotation databases

机译:重温Babel塔:跨注释数据库进行交叉引用的通用资源

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Motivation: Annotation databases are widely used as public repositories of biological knowledge. However, most of these resources have been developed by independent groups which used different designs and different identifiers for the same biological entities. As we show in this article, incoherent name spaces between various databases represent a serious impediment to using the existing annotations at their full potential. Navigating between various such name spaces by mapping IDs from one database to another is a very important issue which is not properly addressed at the moment. Results: We have developed a web-based resource, Onto-Translate (OT), which effectively addresses this problem. OT is able to map onto each other different types of biological entities from the following annotation databases: Swiss-Prot, TrEMBL, NREF, PIR, Gene Ontology, KEGG, Entrez Gene, GenBank, GenPept, IMAGE, RefSeq, UniGene, OMIM, PDB, Eukaryotic Promoter Database, HUGO Gene Nomenclature Committee and NetAffx. Currently, OT is able to perform 462 types of mappings between 29 different types of IDs from 17 databases concerning 53 organisms. Among these, over 300 types of translations and 15 types of IDs are not currently supported by any other tool or resource. On average, OT is able to correctly map between 96 and 99% of the biological entities provided as input. In terms of speed, sets of similar to 20 000 IDs can be translated in < 30 s, in most cases.
机译:动机:注释数据库被广泛用作生物知识的公共资源库。但是,大多数这些资源是由独立的小组开发的,这些小组对同一生物实体使用不同的设计和不同的标识符。正如我们在本文中所展示的,各种数据库之间不连贯的名称空间严重阻碍了充分利用现有注释的潜力。通过将ID从一个数据库映射到另一个数据库,在各种这样的名称空间之间导航是一个非常重要的问题,目前尚无法正确解决。结果:我们开发了一个基于Web的资源Onto-Translate(OT),可以有效解决此问题。 OT可以从以下注释数据库中相互映射到不同类型的生物实体:Swiss-Prot,TrEMBL,NREF,PIR,Gene Ontology,KEGG,Entrez Gene,GenBank,GenPept,IMAGE,RefSeq,UniGene,OMIM,PDB ,真核启动子数据库,HUGO基因命名委员会和NetAffx。目前,OT能够从涉及53种生物的17个数据库中的29种不同类型的ID之间执行462种映射。其中,目前尚无任何其他工具或资源支持300多种翻译和15种ID。平均而言,OT能够正确映射提供作为输入的96%至99%的生物实体。在速度方面,大多数情况下,可以在不到30秒的时间内转换相似的20000个ID的集合。

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