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中文摘要
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方法1。网络分析和可视化:我们将通过开发数据分析工具和数据库,以及与外部合作者一起参与项目的数据分析来支持这四个研究主题。我们将为基因组和蛋白质组学数据的分析提供持续的支持。基因组学和蛋白质组学数据的初步分析将在这些设施内进行,以确定由各种扰动引起的统计差异。一旦这些变化被确定,差异调节的基因/蛋白质将被用于开发网络,主题1中的分类器和这些分析的数据将被转移到Core中进行可视化和分发给研究社区。
英文摘要
Approach 1. Network Analysis and Visualization: We will support the four research themes by developing data analysis tools and databases, as well as by participating in data analysis for projects with external collaborators. We will provide ongoing support for analysis of genomic and proteomic data. Initial analysis of the genomic and proteomic data to identify statistical differences caused by the various perturbations will be done within these facilities. Once the changes are identified, the differentially modulated gene/proteins will be used to develop networks, and classifiers in Theme 1 and the data from these analyses will be transferred to the Core for visualization and distribution to the research community. We will continue the development of web-based applications to support interactive visualization of networks and dynamical models. We have extensive experience in the development and distribution of such web based programs as have been described in the Progress Report Section (19, 21, 24, 26, 27, 29-32, 47, 50). In the coming term we will use newer technologies such as HTML5 including the implementation of the features offered by D3, a new JavaScript library for data visualization. We will maintain a mySQL database that contains information about drug properties, drug-drug networks, gene properties, gene regulatory networks, protein-protein interactions, protein kinase-substrate interactions, cell signaling networks and data from quantitative dynamical models. In addition, since HTML5 offers easy Mobile integration we will launch several of the web-based applications for Mobile use as phone and tablet Apps. As part of the research themes we plan to develop a web-interface for the drug/side-effect classifier proposed for Theme 1. We will develop web visualization for the both the underlying networks and the dynamical models that will be developed in Themes 2 and 3. This will enable the wide dissemination of these models so that they can be used by others. For Theme 4 we will develop the heart 3D models as an interactive online tool where users will be able to tune parameters and run simulations online.
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Predicting determinants of susceptibility to drug-induced arrhythmias
Computational methods for mechanistic understanding of inter-sample variability
Core 1
Core 1
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