Biostatistics and Data Science Core

生物统计学和数据科学核心

• 批准号: 10393301
• 负责人: Li Luo
• 金额: $ 11.81万
• 依托单位: UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-25 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10393301
• 关键词: Biometry; Data Science Core; Environmental Science; New Mexico; Research; Science; programs

Biostatistics and Data Science Core (BDSC) - Project Summary The objective of the BDSC is to provide state-of-the-art support in data management, high dimensional complex data science and bioinformatics, and cutting-edge biostatistical and geospatial analysis to meet the data management and analysis challenges of working with environmental exposure mixtures, and to advance the environmental health research performed by the NM-INSPIRES Center investigators. The BDSC will be co- led by Drs. Li Luo and Yan Guo. Dr. Luo has over 10 years of experience in high dimensional data analysis, environmental chemical mixture modeling, causal inference, genetic-environment interaction and integrative analysis, and statistical analysis of data from large scale population-based epidemiological and clinical studies. Dr. Luo has lead the data management and analysis team supporting multiple NIH-funded environmental health research projects and programs for over 3 years. Dr. Guo is a Bioinformatics expert who is the Director of the Bioinformatics Shared Resources at the University of New Mexico Comprehensive Cancer Center. Dr. Guo’s research has been focused on the development of bioinformatics methodology and analysis approaches for cancer genomic studies and has published more than 150 manuscripts in the related fields. Core members include eight quantitative scientists with complementary expertise in data management and analysis for a variety of scientific domains. Core members have backgrounds and expertise in a wide range of quantitative research methodologies, including modern FAIR compliant data management, biostatistical methods, bioinformatics tools, geospatial analysis and modeling, survey data analysis, Bayesian methods, and causal inference. The team members have collaborated for many years on multiple environmental health projects, and have streamlined the workflow from data collection, quality control, bioinformatics, biostatistical and geospatial analysis support, and methodology developments to enhance the analysis of environmental health data sets. The Core will serve as a hub for all research activities of the Center and provide a wide array of analytical support to Center investigators engaging in environmental health research. The BDSC support will contribute to many aspects of the research process including, but not limited to, efficient study design, appropriate monitoring of data security, enhanced data management capacity, state-of-the-art bioinformatics, biostatistical and geospatial analyses, assistance in the development of study protocols and proposals, as well as sample size and power calculations. Core faculty will also provide educational opportunities to Center investigators and trainees through lectures, classroom teaching, workshops, and hands-on training. The collaborative efforts of Core members will contribute not only to effectively pursuing hypothesis-driven research questions but also to developing novel research questions through complex analyses of large datasets. BDSC is well positioned to promote multidisciplinary and interdisciplinary research and develop analytical strategies to contribute to the successful completion of basic, community-based, and translational research projects within the Center.

生物统计学和数据科学核心（BDSC）-项目摘要 BDSC的目标是提供最先进的数据管理支持， 复杂的数据科学和生物信息学，以及尖端的生物统计和地理空间分析，以满足 数据管理和分析挑战的工作与环境接触的混合物，并推动 NM-INSPIRES中心研究人员进行的环境健康研究。BDSC将共同- 由罗力博士和郭艳博士带领。罗博士在高维数据分析方面拥有超过10年的经验， 环境化学混合物模型，因果推理，遗传-环境交互作用和综合 分析和统计分析的数据，从大规模的人口为基础的流行病学和临床研究。 博士Luo领导的数据管理和分析团队支持多个NIH资助的环境 3年以上的健康研究项目和方案。郭博士是生物信息学专家， 新墨西哥州大学综合癌症中心的生物信息学共享资源。博士 郭的研究重点是生物信息学方法和分析方法的发展 癌症基因组研究，并已发表150多篇相关领域的手稿。核心成员 包括八名在数据管理和分析方面具有互补专长定量科学家， 各种科学领域。核心成员具有广泛的定量分析背景和专业知识， 研究方法，包括现代FAIR合规数据管理，生物统计方法， 生物信息学工具、地理空间分析和建模、调查数据分析、贝叶斯方法和因果关系 推论团队成员在多个环境健康项目上合作多年， 简化了从数据收集、质量控制、生物信息学、生物统计学和地理空间 分析支持和方法发展，以加强对环境健康数据集的分析。 该核心将作为中心所有研究活动的枢纽，并提供广泛的分析 支持中心研究人员从事环境健康研究。BDSC的支持将有助于 研究过程的许多方面，包括但不限于有效的研究设计，适当的 监测数据安全，增强数据管理能力，最先进的生物信息学，生物统计学 地理空间分析，协助制定研究方案和建议，以及样本 大小和功率计算。核心教师还将为中心的研究人员提供教育机会， 通过讲座、课堂教学、讲习班和实践培训，培训学员。的协作努力 核心成员将不仅有助于有效地追求假设驱动的研究问题， 通过对大型数据集的复杂分析来开发新的研究问题。BDSC处于有利地位， 促进多学科和跨学科研究，并制定分析战略， 成功完成中心内的基础、社区和转化研究项目。