DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells.
DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells.
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DOI：
10.1186/1745-7580-6-10
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发表时间：
2010-11-19
期刊：
影响因子：
--
通讯作者：
Austyn, Jonathan M
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文献类型：
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作者：
Cavalieri, Duccio;Rivero, Damariz;Austyn, Jonathan M
背景：系统生物学的出现伴随着路径数据库的蓬勃发展。目前的途径一般是根据发生反应的器官或细胞类型来定义的。反应的细胞类型特异性是免疫学研究的基础，当使用基于通路的分析来破译复杂的免疫学数据集时，捕获这种特异性是至关重要的。在这里，我们提出了DC-ATLAS，一种新的和通用的资源，用于解释干扰树突状细胞（dc）信号网络产生的高通量数据。结果：通路使用一种新的数据模型进行注释，即生物连接标记语言（BCML），这是一种符合sbgn的数据格式，用于存储收集到的大量信息。DC-ATLAS应用于基于通路的分析，分析受toll样受体家族激动剂刺激的dc的转录程序，可以对从细胞传感器到功能结果的信息流进行综合描述，通过对在定义良好的功能模块中不同时间点发生的反应集进行分组，捕获激活事件的时间序列。结论：该倡议显著提高了我们对DC生物学和调控网络的理解。开发免疫系统的系统生物学方法有望将免疫系统知识转化为更成功的免疫治疗策略。
BACKGROUND: The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs).RESULTS: Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules.CONCLUSIONS: The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies.