Core 1

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，以及通过参与与外部合作者的项目数据分析来支持四个研究主题。我们将为基因组和蛋白质组数据的分析提供持续的支持。将在这些设施内对基因组和蛋白质组数据进行初步分析，以确定各种扰动引起的统计学差异。一旦确定了这些变化，差异调节的基因/蛋白质将用于开发网络，主题1中的分类器和来自这些分析的数据将被转移到核心，以便可视化和分发给研究界。 我们将继续开发基于Web的应用程序，以支持网络和动态模型的交互式可视化。我们在开发和分发此类基于Web的程序方面拥有丰富的经验，如进度报告部分（19，21，24，26，27，29-32，47，50）所述。在下一学期，我们将使用更新的技术，如HTML5，包括D3提供的功能的实现，D3是一个新的JavaScript库，用于数据可视化。我们将维护一个mySQL数据库，其中包含有关药物性质、药物-药物网络、基因性质、基因调控网络、蛋白质-蛋白质相互作用、蛋白激酶-底物相互作用、细胞信号传导网络和定量动力学模型数据的信息。此外，由于HTML5提供了简单的移动的集成，我们将推出几个基于Web的应用程序，用于移动的手机和平板电脑应用程序。作为研究主题的一部分，我们计划为主题1提出的药物/副作用分类器开发一个网络界面。我们将为主题2和主题3中开发的底层网络和动态模型开发Web可视化。这将使这些模式得到广泛传播，以便其他人可以使用。对于主题4，我们将开发心脏3D模型作为交互式在线工具，用户可以在线调整参数并运行模拟。

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.