PhosphoExplorer: Software for annotating and analyzing phosphoproteomics data

PhosphoExplorer：用于注释和分析磷酸蛋白质组学数据的软件

• 批准号: 9176205
• 负责人: MARK R CHANCE
• 金额: $ 36.02万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9176205
• 关键词: Affinity; Amino Acid Sequence; Amino Acids; Antibodies; Biological; Biological Sciences; Biology; Communicable Diseases; Communities; Computer software; Data; Data Collection; Data Set; Databases; Development; Disease; Effectiveness; Exhibits; Feedback; Gene Expression; Gene Expression Profiling; Goals; Grant; Housing; Human; Institutes; Knowledge; Letters; Malignant Neoplasms; Mass Spectrum Analysis; Metals; Methods; Neurosciences; Outcomes Research; Pathway Analysis; Pathway interactions; Peptide Sequence Determination; Peptides; Pharmaceutical Preparations; Phosphopeptides; Phosphoproteins; Phosphoric Monoester Hydrolases; Phosphorylation; Phosphorylation Site; Phosphotransferases; Protein Analysis; Protein Kinase; Protein phosphatase; Proteins; Proteome; Research; Role; Sampling; Science; Scientist; Signal Pathway; Signal Transduction; Site; Software Tools; Suggestion; System; Systems Biology; Technology; Testing; Time; Translations; Uncertainty; Universities; Validation; abstracting; cohort; computerized tools; design; drug development; improved; insight; novel; open source; phosphoproteomics; programs; protein expression; protein function; prototype; research study; search engine; signal processing; simulation; tool

Abstract Phosphoproteomics (PP) data derived from mass spectrometry experiments has a unique ability to interrogate cellular signaling pathways and networks in a comprehensive manner. Such information on a global scale will provide unique insights into cellular signaling in development and differentiation, which will considerably advance our understanding of biology. Although technologies for collecting PP data using mass spectrometry are advancing rapidly, computational tools for analyzing the PP data are not keeping pace. The management and annotation of information on thousands of phosphosites is ineffective if conducted manually and must be automated and visually presented to the user. In addition, although many effective tools exist for pathway and network analysis of gene and protein expression data, the tools for PP are relatively underdeveloped. This proposal, submitted under PA-14-155, intends to advance the field of PP by developing, testing, and disseminating software for phosphoprotein and phosphosite identification, localization, annotation, pathway and network analysis. The outcome of this research will be more rapid and effective translation of PP data into useful knowledge for advancing biological science and drug development. The research will comprise 3 Aims: Aim 1: Development and testing of PhosMS-GF+ and PhosphoExplorer, a tool for phosphosite identification and annotation from mass spectrometry data. This aim will provide a tool that can unify mass spectrometry data with multiple phosphosite databases and extend the number of PP identifications improving analyses. Aim 2: Development and testing of a phosphoprotein set enrichment analysis tool kit and phosphoprotein interaction and network analysis tool kit as expansions of PhosphoExplorer. This aim will provide an unique toolkit for systems level analysis of PP data. Aim 3: Develop, test, calibrate, and release software tools for systems-level annotation and analysis of phosphoproteomics data. This aim will deliver robust open-source software to the user community. As prototype versions of PhosphoExplorer currently exist and are in use in-house at Case Western Reserve University, we have no doubt that over a three-year period we can complete the above improvements and put the tools in the hands of a national cohort of users that are actively collecting and analyzing PP datasets.

抽象的 从质谱实验得出的磷蛋白质组学（PP）数据具有独特的能力 以全面的方式询问细胞信号通路和网络。这样的 全球范围的信息将为开发中的细胞信号传导提供独特的见解 和分化，这将大大提高我们对生物学的理解。虽然 使用质谱法收集PP数据的技术正在迅速发展， 用于分析PP数据的计算工具无法保持步伐。管理层和 如果手动进行有关数千种磷岩的信息注释是无效的，并且 必须自动化并在视觉上呈现给用户。此外，尽管许多有效的工具 存在用于基因和蛋白质表达数据的途径和网络分析，PP的工具为 相对欠发达。根据PA-14-155提交的该提案打算推进 通过开发，测试和传播用于磷蛋白和的软件的PP领域 磷材料识别，定位，注释，途径和网络分析。结果 这项研究将更快，有效地转化为PP数据为有用的知识 推进生物科学和药物开发。 该研究将包括3个目标： AIM 1：Phosms-GF+和Phoshoexplorer的开发和测试，磷酸化的工具 质谱数据的识别和注释。这个目标将提供一个可以 用多个磷材料数据库统一质谱数据，并延长数量 PP标识改善了分析。 目标2：开发和测试磷蛋白集富集分析工具套件和 磷酸蛋白相互作用和网络分析工具套件作为磷酸化塑料的扩展。 该目标将为PP数据的系统级分析提供独特的工具包。 目标3：开发，测试，校准和发布用于系统级注释的软件工具， 磷蛋白质组学数据的分析。这个目标将为强大的开源软件提供给 用户社区。 由于当前存在磷酸化的原型版本，并且在内部使用 西部储备大学，我们毫无疑问，在三年内我们可以完成 上述改进，并将工具掌握在全国用户同类的手中 积极收集和分析PP数据集。