LEAPS-MPS: Artificial Intelligence Techniques for Automatic NMR Metabolomics Data Processing

LEAPS-MPS：用于自动 NMR 代谢组学数据处理的人工智能技术

基本信息

批准号：
2137575
负责人：
Bo Wang
金额：
$ 24.86万
依托单位：
North Carolina Agricultural & Technical State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-15 至 2022-11-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137575&HistoricalAwards=false
关键词：
LEAPS MPS Artificial Intelligence Techniques

项目摘要

This award is funded in part under the American Rescue Plan Act of 2021 (Public Law 117-2). In this project, funded by the Mathematical and Physical Sciences Directorate and the Chemistry Division, Professor Bo Wang and his students at North Carolina Agricultural & Technical State University (NCAT) will develop tools for analysis of chemical data that would be easier to apply for non-specialists. The data are related to environmental and health studies and will be obtained using Nuclear Magnetic Resonance (NMR) methods. The novel way of data processing will use artificial intelligence (AI) methods. This research could have significant impacts on health monitoring by providing fast analysis of complicated data sets. The research is likely to inspire students at the PI's institution, which is a Historically Black College or University (HBCU). Prof. Wang’s plans for broadening participation in STEM by underrepresented minority (URM) students include introducing students to applied data science and AI methods, which are very marketable job skills but are not taught regularly at the undergraduate level. Opportunities for independent interdisciplinary research projects will be provided and a new course will be developed.The identification of metabolites will be improved using AI techniques applied to analysis of 1D and 2D NMR data. NMR has high instrument reliability, but there is a common problem of data overfitting. This new method will provide improved ways for extracting peaks in complex spectra. Training data are freely available from published literature and Prof. Wang’s own studies, and the method will be tested with data recorded by Professor Wang’s group. Methods developed will help make metabolomics and other sophisticated NMR-based research accessible to a broader range of scientists. This research will be integrated with education through course and curriculum development, and the introduction of an educational website. Summer workshops will also be conducted. ucted.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.

该奖项是根据2021年《美国救援计划法》（第117-2）的部分资助。在该项目中，由数学和物理科学局和化学部门资助，Bo Wang教授及其学生在北卡罗来纳州农业技术州立大学（NCAT）将开发用于分析化学数据的工具，这些工具可以更容易申请非专家。数据与环境和健康研究有关，将使用核磁共振（NMR）方法获得。新颖的数据处理方式将使用人工智能（AI）方法。这项研究可以通过对复杂数据集的快速分析对健康监测产生重大影响。该研究可能会激发PI机构的学生，即历史悠久的黑人学院或大学（HBCU）。王教授的计划扩大了代表性不足的少数民族（URM）学生的计划，包括向学生介绍应用数据科学和AI方法，这些方法是非常有市场的工作技能，但并未在本科层面上定期教授。将提供独立的跨学科研究项目的机会，并将开发新的课程。使用用于分析1D和2D NMR数据的AI技术，将改善代谢物的识别。 NMR具有较高的仪器可靠性，但是数据的常见问题过于拟合。这种新方法将提供改进的方法来提取复杂光谱中的峰值。培训数据可从已发表的文献和Wang教授的研究中免费获得，该方法将通过Wang教授小组记录的数据进行测试。开发的方法将有助于使代谢组学和其他基于NMR的其他复杂研究可用于更广泛的科学家。这项研究将通过课程和课程开发与教育联系，并引入一个教育网站。还将举办夏季研讨会。 ucted。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估被认为是宝贵的支持。