Visual Analytics Software Environment for Proteomics Data Integration

近年来，基于基因组的技术的发展和可获得性已经 将分析研究推向生物学的前沿。一种理想的系统级生物学方法 研究是在计算和实验之间反复进行的。显式，通过使用 基于计算、统计和可视化的技术来询问数据，新 实验假说可以开发出来，然后在实验室中进行测试。然而， 高通量方法生成的数据量和异构性创造了一个 需要开发改进的数据整合和解释方法。 这项提议的重点是继续发展和维护我们现有的视觉 分析软件：蛋白质组学多肽和蛋白质数据探索平台(PQuad)，a 目前可以集成基因组和蛋白质组数据的多分辨率环境 原核生物数据集。PQuad目前具有识别差异表达的能力 两个实验之间的多肽和蛋白质，并执行分类的基本数据集成 信息。在原核系统中对多条证据的询问立即 鉴定病原菌中毒力决定因素的意义。我们建议继续 PQuad在两个核心领域的开发：(1)高级用户交互和(2)增强 视觉化。 具体目标#1：开发高级用户界面，引导用户 上传多个信息源(实验和元数据)，执行查询 以针对感兴趣的特定生物分子，并导出感兴趣的特定查询以供进一步 在PQuad之外的探索。此外，我们还将提供执行基本统计的能力 可用于阈值查询的基于MS的蛋白质组肽鉴定分析 和视觉化。 具体目标2：开发新的可视化以支持分析和 数据源和查询的集成。新的视觉范例将被纳入到 软件，这些软件不是以基因组为中心的，而是旨在促进对 可用数据源或目标1中定义的特定查询。 通过与NIAID资助的生物防御蛋白质组之一相关的用户合作 研究中心(http://www.proteomicsresource.org/PRC/About.aspx)，我们将演示 数据集成能力，最终目标是发现沙门氏菌的毒力决定因素

In recent years, the development and availability of omic-based technologies has moved analytical research to the forefront of biology. A desirable approach to systems-level biology research is to iterate between computation and experimentation. Explicitly, by using computational, statistical, and visualization-based techniques to interrogate the data, new experimental hypotheses can be developed and subsequently tested in the laboratory. However, the volume and heterogeneity of data being generated by high-throughput methods has created a need to develop improved methods for data integration and interpretation. The focus of this proposal is the continued development and maintenance of our existing visual analytics software: Platform for Proteomics Peptide and Protein data exploration (PQuad), a multi-resolution environment that can currently integrate genomic and proteomic data for complex prokaryotic datasets. PQuad currently has the capability to identify differentially expressed peptides and proteins between two experiments, and perform basic data integration of categorical information. The interrogation of multiple lines of evidence in prokaryotic systems has immediate significance for identifying virulence determinants in pathogens. We propose to continue the development of PQuad in two core areas: (1) advanced user-interaction and (2) enhanced visualizations. Specific Aim #1: The development of an advanced user-interface that will guide users in uploading multiple sources of information (both experimental and metadata), performing queries to target specific biomolecules of interest, and export specific queries of interest for further exploration outside of PQuad. In addition, we will offer the ability to perform basic statistical analyses of MS-based proteomic peptide identifications that can be used for thresholding queries and visualizations. Specific Aim #2: The development of new visualizations to support analysis and integration of data sources and queries. New visual paradigms will be incorporated into the software, which are not genome-centric, but targeted at facilitating the biological interpretation of available data sources or specific queries as defined in Aim 1. Through collaboration with users associated with one of the NIAID-funded Biodefense Proteomics Research Centers (http://www.proteomicsresource.org/PRC/About.aspx), we will demonstrate the data integration capabilities with the end goal of virulence determinant discovery in Salmonella