Biostatistics and Data Science Core

生物统计学和数据科学核心

基本信息

批准号：
10689687
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
项目类别：
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/10689687
关键词：
Accounting Air Pollutants Basic Science Bayesian Method Bioinformatics Bioinformatics Shared Resource Biometry Biostatistical Methods Cardiovascular Diseases Characteristics Chemistry Clinical Research Collaborations Communication Communities Community Health Complex Complex Analysis Complex Mixtures Comprehensive Cancer Center Data Data Analyses Data Analytics Data Collection Data Science Data Science Core Data Security Data Set Databases Development Dimensions Disease Dose Education Educational process of instructing Educational workshop Ensure Environment Environmental Exposure Environmental Health Environmental Science Etiology FAIR principles Faculty Funding Generations Genetic Genomics Geographic Information Systems Health Infectious Agent Infrastructure Interdisciplinary Study Intervention Knowledge Lead Life Cycle Stages Malignant Neoplasms Manuscripts Metal exposure Methodology Methods Modeling Modernization Monitor New Mexico Nutrient Outcome Pathway interactions Physical activity Policy Making Population Study Positioning Attribute Practice Management Prevention strategy Process Protocols documentation Publishing Quality Control Research Research Activity Research Design Research Methodology Research Personnel Research Project Grants Risk Assessment Risk Factors Role Sample Size Science Scientist Services Statistical Data Interpretation Surveys Techniques Testing Training Translational Research United States National Institutes of Health Universities Visualization software Work analytical method bioinformatics pipeline bioinformatics tool cancer genomics citizen science complex data data hub data infrastructure data management design dietary environmental chemical epidemiology study experience exposure pathway high dimensionality improved insight large datasets large scale data lectures member metabolomics method development microbiome research multidimensional data multidisciplinary novel population based programs response statistical and machine learning tool transcriptomics

项目摘要

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的目的是在数据管理中提供最新的支持，高维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与环境暴露混合物合作的挑战，并推进 NM启发中心研究人员进行的环境健康研究。 BDSC将是由博士领导。 Li Luo和Yan Guo。 Luo博士在高维数据分析方面拥有10多年的经验，环境化学混合物建模，因果推断，遗传环境相互作用和综合性分析和统计分析基于大规模的流行病学和临床研究的数据。 Luo博士领导数据管理和分析团队，支持多个NIH资助的环境健康研究项目和计划已有3年以上。 Guo博士是一位生物信息学专家，是董事在新墨西哥大学综合癌症中心共享了生物信息学的资源。博士郭的研究集中在生物信息学方法论和分析方法的发展上用于癌症基因组研究，并在相关领域发表了150多种手稿。核心成员包括八位具有数据管理专业知识和分析的定量科学家各种科学领域。核心成员具有广泛定量的背景和专业知识研究方法，包括现代公平的数据管理，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理。团队成员在多个环境健康项目上合作了多年，已经简化了数据收集，质量控制，生物信息学，生物统计学和地理空间的工作流程分析支持和方法发展，以增强环境健康数据集的分析。核心将作为中心所有研究活动的枢纽，并提供各种各样的分析支持中心研究人员从事环境健康研究。 BDSC支持将贡献在研究过程的许多方面，包括但不限于有效的研究设计，适当监视数据安全性，增强数据管理能力，最先进的生物信息学，生物统计学以及地理空间分析，研究方案和建议的发展以及样本尺寸和功率计算。核心教师还将为中心调查人员提供教育机会和通过讲座，课堂教学，讲习班和动手培训的学员。的协作努力核心成员将不仅为有效地追求假设驱动的研究问题做出贡献通过对大型数据集进行复杂的分析来开发新的研究问题。 BDSC的位置很好促进多学科和跨学科研究，并制定分析策略以促进成功完成了中心内基于社区和翻译的研究项目。