Visual Analytics Software Environment for Proteomics Data Integration

用于蛋白质组学数据集成的可视化分析软件环境

• 批准号: 7943075
• 负责人: BOBBIE-JO Mary WEBB-ROBERTSON
• 金额: $ 47.46万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7943075
• 关键词: Advanced Development; Algorithms; Area; Biological; Biology; Collaborations; Color; Communities; Complex; Computer software; Data; Data Analyses; Data Set; Data Sources; Development; Drug resistance; Environment; Funding; Gene Expression; Generations; Genome; Genomics; Goals; Heating; Heterogeneity; Imagery; Immune response; Laboratories; Link; Maintenance; Maps; Mass Spectrum Analysis; Metadata; Methods; Mining; Peptides; Play; Prokaryotic Cells; Proteins; Proteomics; Research; Research Personnel; Resolution; Resources; Role; Salmonella; Salmonella typhimurium; Source; System; Systems Biology; Techniques; Technology; Testing; Virulence; Visual; Work; base; biodefense; biological systems; comparative; data integration; high throughput technology; improved; innovation; interest; novel therapeutics; pathogen; research study; resistance mechanism; software development; therapeutic target; tool; user friendly software

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

近年来，基于omic的技术的开发和可用性已经发生了变化， 生物学前沿的分析研究。系统级生物学的理想方法 研究是在计算和实验之间进行的。解释，通过使用 计算，统计和可视化为基础的技术来询问数据，新的 实验假设可以发展，并随后在实验室进行测试。然而，在这方面， 由高通量方法生成的数据的量和异质性已经产生了 需要制定更好的数据整合和解释方法。 这项建议的重点是继续发展和维持我们现有的视觉 分析软件：蛋白质组学肽和蛋白质数据探索平台（PQuad）， 多分辨率环境，目前可以整合基因组和蛋白质组数据， 原核生物数据集。PQuad目前有能力识别差异表达的 两个实验之间的肽和蛋白质，并执行分类的基本数据整合 信息.在原核系统中对多条证据的审问， 鉴定病原体毒力决定因子的意义。我们建议继续 在两个核心领域开发PQuad：（1）高级用户交互和（2）增强 可视化。 具体目标#1：开发一个先进的用户界面，引导用户 上传多个信息源（实验和元数据），执行查询 以目标特定的感兴趣的生物分子，并导出感兴趣的特定查询，以进一步 探索PQuad以外的地方此外，我们将提供执行基本统计的能力， 基于MS的蛋白质组肽鉴定分析，可用于阈值查询 和可视化。 具体目标#2：开发新的可视化工具来支持分析和 数据源和查询的集成。新的视觉范例将被纳入 软件，不是以基因组为中心的，但旨在促进生物学解释， 目标1中定义的可用数据源或特定查询。 通过与NIAID资助的生物防御蛋白质组学之一相关的用户合作， 研究中心（http：//www.proteomicsresource.org/PRC/About.aspx），我们将展示 数据集成能力，最终目标是发现沙门氏菌的毒力决定簇

项目成果

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data.

• DOI: 10.1186/1471-2164-13-131
• 发表时间: 2012-04-05
• 期刊: BMC genomics
• 影响因子: 4.4
• 作者: Peterson ES;McCue LA;Schrimpe-Rutledge AC;Jensen JL;Walker H;Kobold MA;Webb SR;Payne SH;Ansong C;Adkins JN;Cannon WR;Webb-Robertson BJ
• 通讯作者: Webb-Robertson BJ