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EcID:一个用于推断大肠杆菌中功能相互作用的数据库。

EcID. A database for the inference of functional interactions in E. coli.

作者信息

Andres Leon Eduardo, Ezkurdia Iakes, García Beatriz, Valencia Alfonso, Juan David

机构信息

Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre-CNIO and Computer Sciences Department, Universidad Carlos III de Madrid, Spain.

出版信息

Nucleic Acids Res. 2009 Jan;37(Database issue):D629-35. doi: 10.1093/nar/gkn853. Epub 2008 Nov 12.

Abstract

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.

摘要

EcID数据库(大肠杆菌相互作用数据库)提供了一个框架,用于整合从以下来源提取的功能相互作用信息:EcoCyc(代谢途径、蛋白质复合物和调控信息)、KEGG(代谢途径)、MINT和IntAct(蛋白质相互作用)。它还包括来自两项大肠杆菌高通量下拉实验的蛋白质复合物信息,以及使用与iHOP文本挖掘系统相关的网络服务从文献中提取的潜在相互作用。此外,EcID纳入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)以及三种基于共进化分析的方法(镜像树、计算机模拟双杂交和上下文镜像)。EcID为每个预测关联一个专门开发的置信度分数。使EcID与其他系统不同的两个主要特征是基于共进化的预测与实验数据的结合,以及引入大肠杆菌特异性信息,如来自EcoCyc的基因调控信息。通过对一组与yeaG相关的特征不明确的基因的潜在功能预测,展示了EcID数据库信息组合所提供的可能性。EcID可在http://ecid.bioinfo.cnio.es在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de50/2686479/8639a724b345/gkn853f1.jpg

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