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Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

机译:创建和分析信号传导网络建模的途径和蛋白质相互作用纲要

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摘要

BackgroundUnderstanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID), PANTHER, Reactome, I2D, and STRING). We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data.
机译:背景技术了解信号转导网络的信息处理能力,如何在疾病中破坏这些网络以及合理设计治疗疾病状态的疗法,需要系统准确地重建网络拓扑。在多种途径和相互作用组数据库在线资源(癌症细胞图,GeneGo,KEGG,NCI途径相互作用组数据库(NCI-PID))中可以找到关于人类生理学核心网络的数据,例如此处分析的炎症信号网络。 ,PANTHER,Reactome,I2D和STRING)。我们试图确定这些数据库是否包含重叠信息,以及是否可以将它们用于构建高可靠性的先验知识网络,以用于后续的实验数据建模。

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