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首页> 外文期刊>Nucleic Acids Research >EcID. A database for the inference of functional interactions in E. coli.
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EcID. A database for the inference of functional interactions in E. coli.

机译:EcID。推断大肠杆菌中功能相互作用的数据库。

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The EcID database (Escherichia coli Interaction Database) provides a framework for the integration of information on functional interactions extracted from the following sources: EcoCyc (metabolic pathways, protein complexes and regulatory information), KEGG (metabolic pathways), MINT and IntAct (protein interactions). It also includes information on protein complexes from the two E. coli high-throughput pull-down experiments and potential interactions extracted from the literature using the web services associated to the iHOP text-mining system. Additionally, EcID incorporates results of various prediction methods, including two protein interaction prediction methods based on genomic information (Phylogenetic Profiles and Gene Neighbourhoods) and three methods based on the analysis of co-evolution (Mirror Tree, In Silico 2 Hybrid and Context Mirror). EcID associates to each prediction a specifically developed confidence score. The two main features that make EcID different from other systems are the combination of co-evolution-based predictions with the experimental data, and the introduction of E. coli-specific information, such as gene regulation information from EcoCyc. The possibilities offered by the combination of the EcID database information are illustrated with a prediction of potential functions for a group of poorly characterized genes related to yeaG. EcID is available online at http://ecid.bioinfo.cnio.es.
机译:EcID数据库(大肠杆菌相互作用数据库)为从以下来源提取的功能相互作用信息的整合提供了一个框架:EcoCyc(代谢途径,蛋白质复合物和调节信息),KEGG(代谢途径),MINT和IntAct(蛋白质相互作用) )。它还包括有关来自两个大肠杆菌高通量下拉实验的蛋白质复合物的信息,以及使用与iHOP文本挖掘系统相关的Web服务从文献中提取的潜在相互作用的信息。此外,EcID结合了各种预测方法的结果,包括两种基于基因组信息的蛋白质相互作用预测方法(系统发育谱和基因邻域)和三种基于协同进化分析的方法(镜像树,In Silico 2 Hybrid和上下文镜像) 。 EcID为每个预测关联一个专门制定的置信度得分。使EcID与其他系统不同的两个主要特征是基于协同进化的预测与实验数据的结合,以及大肠杆菌特有信息的引入,例如EcoCyc的基因调控信息。结合了EcID数据库信息所提供的可能性,并通过预测与yeaG有关的一组特征较差的基因的潜在功能来进行说明。 EcID可从http://ecid.bioinfo.cnio.es在线获得。

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