Bauer-Mehren Anna, Furlong Laura I, Sanz Ferran
Research Unit on Biomedical Informatics (GRIB), IMIM-Hospital del Mar, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Dr Aiguader 88, Barcelona, Spain.
Mol Syst Biol. 2009;5:290. doi: 10.1038/msb.2009.47. Epub 2009 Jul 28.
In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signalling networks, which ultimately sheds light on the mechanisms leading to complex diseases or helps in the identification of drug targets. A variety of databases containing information on cell signalling pathways have been developed in conjunction with methodologies to access and analyse the data. In principle, the scenario is prepared to make the most of this information for the analysis of the dynamics of signalling pathways. However, are the knowledge repositories of signalling pathways ready to realize the systems biology promise? In this article we aim to initiate this discussion and to provide some insights on this issue.
在过去的几年里,通过从文献中人工整理已经构建了细胞信号通路的综合表示,这需要巨大的努力,并且借助数据库中存储的信息以及自动检索和整合方法会更有成效。一旦实现了相互作用网络的重建,就可以对其结构特征和动态行为进行分析。数学建模技术用于模拟细胞信号网络的复杂行为,这最终有助于揭示导致复杂疾病的机制或有助于识别药物靶点。已经开发了各种包含细胞信号通路信息的数据库,并结合了访问和分析数据的方法。原则上,已经做好了充分利用这些信息来分析信号通路动态的准备。然而,信号通路的知识库是否准备好实现系统生物学的前景呢?在本文中,我们旨在发起这一讨论,并就这个问题提供一些见解。