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EarthCube Data Capabilities: Expanding the Ocean Protein Portal Capabilities for Use in Biochemical Research and Education

EarthCube Data Capabilities: Expanding the Ocean Protein Portal Capabilities for Use in Biochemical Research and Education
EarthCube 数据功能:扩展海洋蛋白质门户功能,用于生化研究和教育
批准号:
2026933
负责人:
Mak Saito
金额:
$60.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-01 至 2024-08-31

项目摘要

项目成果

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中文摘要
翻译
该项目旨在扩展海洋蛋白质门户(OPP)的功能,用于海洋生物化学的研究和教育。海洋蛋白质门户原型的设计是为了让广泛的科学家和学生找到以下问题的答案:1)“我感兴趣的蛋白质在海洋中的哪里”,2)“是谁制造的蛋白质?”通过最少共同祖先的分析,以及3)“有多少?”通过使包括生物和化学海洋学家、地球生物学家、微生物学家、生物化学家和生物无机化学家在内的广泛多领域社区能够访问和搜索海洋蛋白质数据集,我们将提高对海洋和微生物生物化学的理解。此外,这些大型数据集有可能为未来的科学家提供环境变化的重要记录,因此该门户网站用于捕获、组织和共享这些数据,以实现长期的海洋变化能力。该项目的其他好处包括通过提供数据储存库和激励正在进行的改进数据质量和标准的努力,促进海洋变蛋白质组界内的社区建设。这个项目的技术目标包括对海洋蛋白质门户网站的具体改进,例如扩展搜索能力,增加服务新的元蛋白质组数据类型的能力,实施用于增强互操作性和可持续性的知识图谱系统,创建用于机器可访问搜索的API,进一步连接到外部数据和增强可视化能力,创建可重复和可引用的搜索结果,以及开发具有即时质量控制能力的自动摄取。OPP向知识图谱的转变将进一步促进与海洋生态以外的领域的联系,因为该图谱将与环境科学和生物学中的其他数据资源相联系。此外,OPP知识图还将提供对计算机科学领域有用的数据结构,因为该数据结构立即可用于机器学习和人工智能的应用,从而促进了新的机器辅助科学发现的潜力。研究人员将为参与者提供教程(虚拟或亲自),以了解海洋代谢蛋白质组数据类型,如何使用OPP界面,以及如何从OPP中提取数据并在Jupyter笔记本环境中绘制(使用Python、Matplotlib、Bokeh和Binder)。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to expand the functionality of the Ocean Protein Portal (OPP) for use in research and education on ocean biochemistry. The Ocean Protein Portal prototype was designed to allow a broad range of scientists and students to discover answers to the questions: 1) “Where is my protein of interest in the oceans”, 2) “Who makes the protein?” through least common ancestor analysis, and 3) “How much is there?”. By making ocean protein datasets accessible and searchable to broad multi-domain communities including biological and chemical oceanographers, geobiologists, microbiologists, biochemists, and bioinorganic chemists, our understanding of the oceans and of microbial biochemistry will be improved. Moreover, these large datasets have the potential to provide future scientists with an important record of environmental change, and hence the portal is serving to capture, organize, and share these data to enable long term ocean change capabilities. Additional benefits of this project include contributing to community building within the ocean metaproteome community by providing a data repository and motivating ongoing efforts to improve data quality and standards. Educational use will be developed through collaborations with teachers and professors by the creation of educational modules for students learning about chemical reactions.Technical goals of this project include specific improvements to the Ocean Protein Portal such as expanding search capabilities, adding the ability to serve new metaproteomic data types, implementing a Knowledge Graph system for increased interoperability and sustainability, creating an API for machine accessible searches, furthering connections to external data and enhancing visualization capabilities, creating reproducible and citable search results, and development of automated ingestion with immediate QC capability. The transition of the OPP to a Knowledge Graph will further facilitate connections with domains outside marine ecology, as the graph will link out to other data resources in the environmental sciences and biology. In addition, an OPP Knowledge Graph would also provide a data structure useful to the field of computer science as this data structure is immediately available to applications of Machine Learning and Artificial Intelligence thus advancing the potential for novel machine-assisted scientific discovery. The researchers will conduct tutorials (virtual or in person) for participants to learn about the ocean metaproteomics datatype, how to use the OPP interface, and how to pull data from the OPP and plot it within the Jupyter notebook environment (using Python, Matplotlib, Bokeh, and Binder).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1021/acs.jproteome.3c00152
发表时间: 2023-09-01
期刊: JOURNAL OF PROTEOME RESEARCH
影响因子: 4.4
作者: [Paoletti, Madeline M., Fournier, Gregory P., Dolan, Erin L., Saito, Mak A.]
通讯作者: Saito, Mak A.
DOI: 10.1073/pnas.2200014119
发表时间: 2022-09-13
期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
影响因子: 11.1
作者: [Saunders, Jaclyn K., McIlvin, Matthew R., Dupont, Chris L., Kaul, Drishti, Moran, Dawn M., Horner, Tristan, Laperriere, Sarah M., Webb, Eric A., Bosak, Tanja, Santoro, Alyson E., Saito, Mak A.]
通讯作者: Saito, Mak A.
MRI: Track 1 Acquisition of Instrumentation for Marine Metal-Organic and Metalloproteomic Analyses
AccelNet - Implementation: Development of an International Network for the Study of Ocean Metabolism and Nutrient Cycles on a Changing Planet (Biogeoscapes)
US GEOTRACES GP17-OCE and GP17-ANT: Cobalt Biogeochemical Cycling and Phytoplankton Protein Biomarkers in the Pacific and Southern Oceans
Collaborative Research: Evolutionary, biochemical and biogeochemical responses of marine cyanobacteria to warming and iron limitation interactions
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: