Bridging fields and expanding research opportunities with the timescale of life

弥合不同领域并扩大研究机会与生命的时间尺度

• 批准号: 2318917
• 负责人: Stephen Hedges
• 金额: $ 100万
• 依托单位: Temple University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-15 至 2027-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2318917&HistoricalAwards=false
• 关键词: Bridging; fields; expanding; research; opportunities; Bridging; fields; expanding; research; opportunities

The timescale of life, delineating when species diverged from common ancestors, serves as a framework for understanding biology and is fundamental context for other fields of science such as geology, chemistry, and biomedicine. The advancements in genomics and computing have refined this timescale, resulting in the publication of thousands of evolutionary trees scaled to time, known as timetrees. This project supports the development and expansion of TimeTree, an open-source and unified database that synthesizes these data into a global timetree of life. Users can obtain the divergence time of any two species, a timeline showing all evolutionary splits back in time, and exportable timetrees of any group or from a custom list of species. Events in geological and astronomical history, such as asteroid impacts, oxygen levels, and solar luminosity, are integrated into the same timescale with species timetrees and timelines, facilitating interdisciplinary research and applications in areas like molecular biology, conservation, and medicine. The new TimeTree resource will implement new algorithms, tools, and application programming interfaces to speed, improve, and increase the efficiency of timetree curation and data mining. It will have a new online educational component designed for K-12 and college students, including assignments that demonstrate the principles, models, and methods for building timetrees. Its new graphical interface will be enhanced specifically for use by non-scientists and will include training tools to engage stakeholder communities, allowing for more user feedback. This expanded TimeTree resource aims to stimulate and accelerate research and discovery across diverse scientific disciplines while also serving as a simple-to-use tool for education and outreach. The enhancements in TimeTree will enable researchers worldwide to query, retrieve, visualize, and explore evolutionary patterns, thus aiding hypothesis formulation and augmenting both scientific and societal returns on investments in basic biological research. The newly developed approaches and computational infrastructure will have greater efficiency that will result in the largest timetree of life ever assembled. The incorporation of a novel super-timetree estimation method will yield a more rapid and precise synthesis, affording greater and frequent automated assembly of the super-timetree and updates of the database. For example, a deep-learning approach will be employed to identify and incorporate newly published timetree studies quickly into the database. Beyond these core functionalities, TimeTree aims to bridge scientific disciplines by developing and integrating new tools for data analytics and mining, streamlining the use of complex timetree data. A specialized tool will allow users to access all associated study data for the node of interest, perform analyses on those data, and retrieve the data and results for further offline analyses. Advances in the application programming interface will offer a broader array of functionalities, such as serving commonly used biodiversity metrics. Innovative widgets will interface with other databases to provide them with divergence times and derivative metrics. TimeTree also will also include analytical utilities, such as lineages-through-time and diversification plots, so researchers may immediately see the results for any group. To ensure long-term sustainability while limiting maintenance costs, automated tools for processing and curating published timetrees will be integrated. TimeTree will remain fully open access, with the super-timetree, associated study data, and source code being readily downloadable.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.

生命的时间范围，当物种与共同祖先不同时，描述的是理解生物学的框架，并且是其他科学领域的基本背景，例如地质，化学和生物医学。基因组学和计算的进步已经完善了这个时间尺度，导致出版了成千上万的进化树，被缩放到时间表，称为时间表。该项目支持时间表的开发和扩展，该项目是一个开源和统一数据库，将这些数据综合为全球生活时间表。用户可以获得任何两个物种的分歧时间，时间表显示所有进化的时间分配，以及任何群体或从自定义物种列表中的可出口时间表。地质和天文史上的事件，例如小行星影响，氧气水平和太阳能度，与物种时间表和时间表相同的时间表，促进了跨学科研究以及在分子生物学，保护和医学等地区的应用。新的时间表资源将实施新的算法，工具和应用程序编程界面，以加快，提高和提高时间表策划和数据挖掘的效率。它将有一个新的在线教育组成部分，专为K-12和大学生设计，包括展示建立时间表的原理，模型和方法的任务。它的新图形接口将专门用于非科学家使用，并将包括吸引利益相关者社区的培训工具，从而提供更多用户的反馈。这种扩展的时间表资源旨在刺激和加速各种科学学科的研究和发现，同时也是一种易于使用的教​​育和外展工具。时间表的增强能力将使全世界的研究人员能够查询，检索，可视化和探索进化模式，从而有助于假设表述，并增强基本生物学研究投资的科学和社会回报。新开发的方法和计算基础设施将具有更高的效率，这将导致有史以来最大的生活时间表。新颖的超敏捷估计方法的结合将产生更快，更精确的合成，从而提供超级吉比的更大和频繁的自动组装和数据库的更新。例如，将采用一种深入学习的方法来识别并将新发表的时间表研究迅速纳入数据库。除了这些核心功能之外，时间表还旨在通过开发和集成用于数据分析和采矿的新工具，简化复杂时间表数据的使用来弥合科学学科。一个专业的工具将允许用户访问感兴趣的节点，对这些数据进行分析，并检索数据和结果以进行进一步的离线分析。应用程序编程界面的进步将提供更广泛的功能，例如服务常用的生物多样性指标。创新的小部件将与其他数据库交互，以提供差异时间和派生指标。时间表还将包括分析公用事业，例如直通时间和多样化图，因此研究人员可以立即看到任何组的结果。为了确保长期的可持续性在限制维护成本的同时，将集成用于处理和策划发布的时间表的自动化工具。时间表将保持完全开放的访问权限，具有超级二维，相关的研究数据以及易于下载的源代码。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。