PhosphoExplorer: Software for annotating and analyzing phosphoproteomics data

PhosphoExplorer：用于注释和分析磷酸化蛋白质组数据的软件

• 批准号: 9339710
• 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/9339710
• 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 Profiling; Goals; Grant; Human; Institutes; Knowledge; Letters; Malignant Neoplasms; Manuals; Mass Spectrum Analysis; Metals; Methods; Modernization; Neurosciences; Outcomes Research; Pathway Analysis; Pathway interactions; Peptides; Pharmaceutical Preparations; Phosphopeptides; Phosphoproteins; Phosphoric Monoester Hydrolases; Phosphorylation; Phosphorylation Site; Phosphotransferases; Process; Program Development; 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; cohort; computerized tools; design; drug development; exhaustion; experimental study; improved; insight; novel; open source; phosphoproteomics; protein expression; protein function; prototype; search engine; 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 来自质谱实验的磷酸化蛋白质组学 (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 全球范围内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，这将大大增进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 数据的计算工具没有跟上步伐。管理层和 如果手动进行，对数千个磷酸位点的信息进行注释是无效的 必须自动化并直观地呈现给用户。此外，虽然有很多有效的工具 存在用于基因和蛋白质表达数据的通路和网络分析，PP的工具是 相对不发达。该提案根据 PA-14-155 提交，旨在推进 通过开发、测试和传播磷蛋白和 磷酸位点识别、定位、注释、通路和网络分析。结果 这项研究的目的是将 PP 数据更快速、更有效地转化为有用的知识 推进生物科学和药物开发。 该研究将包括 3 个目标： 目标 1：开发和测试 PhosMS-GF+ 和 PhosphoExplorer（磷酸盐分析工具） 质谱数据的识别和注释。这个目标将提供一个工具，可以 将质谱数据与多个磷酸盐数据库统一起来并扩展 PP 识别改进了分析。 目标 2：开发和测试磷蛋白集富集分析工具包和 磷蛋白相互作用和网络分析工具包，作为 PhosphoExplorer 的扩展。 这一目标将为 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和分析的软件工具 磷酸蛋白质组学数据分析。这一目标将为世界提供强大的开源软件 用户社区。 由于 PhosphoExplorer 的原型版本目前已存在并在 Case 内部使用 西储大学，我们毫不怀疑我们可以在三年内完成 上述改进并将这些工具交到全国用户手中 积极收集和分析 PP 数据集。