Bioinformatics strategies for early life microbiomics

生命早期微生物组学的生物信息学策略

• 批准号: 8928243
• 负责人: Anne Gatewood Hoen
• 金额: $ 11.21万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-29 至 2017-09-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8928243
• 关键词: Address; Award; Bioinformatics; Biological; Biometry; Birth; Boston; Caring; Childhood; Clinical; Clinical Research; Clinical Sciences; Cohort Studies; Communicable Diseases; Communities; Community Health; Complex; Computational Biology; Computer Analysis; Core Facility; DNA Sequence; Data Set; Development; Development Plans; Disease; Doctor of Philosophy; Educational workshop; Ensure; Environment; Epidemiologic Studies; Epidemiologist; Epidemiology; Evaluation; Fill-It; Funding; Genomics; Goals; Graph; Health; Health Benefit; High-Throughput Nucleotide Sequencing; Human; Human Microbiome; Human body; Infant; Infant Health; Infection; Infectious Disease Epidemiology; Informatics; Institutes; Interdisciplinary Study; Intestines; Investigation; Lead; Leadership; Life; Light; Medicine; Mentors; Mentorship; Metagenomics; Methods; Microbe; Molecular; Mothers; Neonatal; Network-based; New Hampshire; Nutritional; Outcome; Parents; Pathway Analysis; Pattern; Pediatric Hospitals; Peer Review; Pregnancy; Professional Ethics; Public Health Informatics; Publications; Qualifying; Recording of previous events; Research; Research Methodology; Research Personnel; Resource Development; Risk; Role; Sampling; Science; Scientist; Series; Stream; Supercomputing; System; Systems Biology; Taxon; Techniques; Technology; Therapeutic Intervention; Time; Training; Translational Research; United States National Institutes of Health; Universities; Work; base; biomedical informatics; career; career development; clinically relevant; cohort; college; computer studies; computerized tools; design; disorder risk; early life exposure; experience; infancy; innovation; lectures; medical schools; meetings; method development; microbial; microbial colonization; microbial community; microbiome; microorganism; multidisciplinary; novel; post-doctoral training; programs; research and development; synergism; tool

DESCRIPTION (provided by applicant): Background. Recent evidence points to the importance of the initial colonization of the human body with microorganisms-the establishment of the microbiome-as a determinant of health outcomes throughout life. The metagenomic technological advances available for characterizing the human microbiome across large cohorts at multiple time points are rapidly out-pacing the computational tools needed to clarify patterns of assembly of the microbiome and investigate connections between observed patterns and health and disease. Network-based methods have immense promise for filling this critical gap, but there are major limitations in the available suie of network analytic tools. The identification of clinically relevant patterns in biological network, and in particular, temporally evolving networks, urgently requires novel methodological approaches. Candidate. Dr. Hoen is a computational epidemiologist mentored by a multidisciplinary team within the Institute for Quantitative Biomedical Sciences (iQBS) and the Geisel School of Medicine at Dartmouth College. With her PhD in infectious disease epidemiology at Yale University and her postdoctoral training in the Children's Hospital Boston Informatics Program/Harvard Medical School, she is extremely well qualified to successfully accomplish her proposed research and career development plan and transition to independence as a scientist in biomedical informatics with the support of this award. Dr. Hoen has an established, productive research background that has resulted in 26 peer-reviewed publications on her interdisciplinary research. Environment. iQBS and the Geisel School of Medicine offer the ideal environment for the proposed career development and research. A collegial intellectual environment, at the core of which is Dr. Hoen's exemplary team of mentors and advisors is bolstered by numerous state-of-the-art research centers and core facilities, including a world-class supercomputing facility. Regular research seminars address current advances in biomedical informatics, genomics and biostatistics, and frequent lecture series in informatics, genomics and medicine attract leading investigators from around the world. Career Development Plan. The goal of this proposal is to gain mentored research experience and career development activities in order to advance Dr. Hoen' career into that of an independent researcher in biomedical informatics. Dr. Hoen's previous research has focused on computational studies of the distribution and determinants of infectious disease risk. She has experience in the analysis of microbial genomic data (doctoral training) and in public health informatics (postdoctoral training). The proposed career development activities and mentored research experience would take Dr. Hoen's expertise to a new level in two distinct ways: (1) by providing her mentored research experience in the development, evaluation and application of novel tools for biomedical informatics research; and (2) by providing her training in biomedical informatics for clinical and translational research. Dr. Hoen proposes to participate in coursework, workshops, seminar series, and research meetings that focus on professional ethics, translational research methods, computational biology including genomics, metagenomics, network analysis, and systems biology. Dr. Hoen has assembled an exemplary mentoring team, led by Dr. Jason Moore, who has a longstanding history of mentorship, leadership, and funded research in biomedical informatics. Her team of mentors and advisors include internationally known experts on informatics methods development, network analysis and complex systems, computational analysis of metagenomic data, clinical and translational science, epidemiology and biomedical informatics leadership. The collective expertise embodied by this team will provide an outstanding resource for the development of Dr. Hoen's career and the successful execution of her multidisciplinary, translational research in biomedical informatics. Dr. Hoen's team is committed to ensuring that she achieves a successful mentored research and career development experience as she works toward independence within the timeframe of this award. Research Plan. The goal of the proposed research is to develop, evaluate and apply computational tools that capture the complexity of large, longitudinal datasets of microbial community composition in conjunction with rich clinical information from a unique ongoing large molecular epidemiologic study using a systems approach that focuses on the complex interactions between human hosts, the communities of bacterial taxa that comprise the microbiome, exposures, health and disease. The framework upon which this research will be built is a series of networks that represent the complex interactions between infants and microbial colonization patterns in light of early life exposures and health-related outcomes. The analyses proposed will address complex patterns captured by these networks including multi-scale associations, multi-way interactions between network components, and temporal dynamics in changing networks. The overarching hypothesis of this research is that these innovative approaches can reveal critical associations between microbiome composition and health and disease in early life. The translational potential of this research lies in novel opportunities to reduce disease risk through therapies that manipulate and preserve a healthy microbiome.

描述（由申请人提供）： 背景。最近的证据表明，人体最初殖民化的重要性是通过微生物 - 建立微生物组，这是整个生命中健康结果的决定因素。可用于表征大型人群在多个时间点的人类微生物组的宏基因组技术进步正在迅速超越阐明微生物组组装模式所需的计算工具，并研究观察到的模式与健康与疾病之间的联系。基于网络的方法填补这一关键差距有很大的希望，但是网络分析工具的可用Suie存在主要局限性。在生物网络中，尤其是时间不断发展的网络中临床相关模式的鉴定，需要新颖的方法学方法。 候选人。 Hoen博士是一名计算流行病学家，由定量生物医学研究所（IQB）和达特茅斯学院（Dartmouth College）的Geisel医学院的多学科团队指导。她在耶鲁大学获得传染病流行病学博士学位，并在波士顿儿童医院在波士顿信息学计划/哈佛医学院接受博士后培训，她非常有资格成功地完成她提出的研究和职业发展计划，并过渡到独立性，成为生物医学信息学科学家，并获得了该奖项的支持。 Hoen博士拥有既定的生产研究背景，在她的跨学科研究中导致了26个经过同行评审的出版物。 环境。 IQB和Geisel医学院为拟议的职业发展和研究提供了理想的环境。众多最先进的研究中心和核心设施（包括世界一流的超级计算设施）支持了Hoen博士的指导者和顾问团队的核心核心。定期的研究研讨会介绍了当前在生物医学信息学，基因组学和生物统计学以及信息学，基因组学和医学方面的频繁讲座系列中的进步，吸引了来自世界各地的主要研究人员。 职业发展计划。该建议的目的是获得指导的研究经验和职业发展活动，以便将Hoen博士的职业发展成为生物医学信息学领域的独立研究人员。 Hoen博士先前的研究重点是关于传染病风险的分布和决定因素的计算研究。她在分析微生物基因组数据（博士培训）和公共卫生信息学（博士后培训）方面有经验。拟议的职业发展活动和指导的研究经验将以两种不同的方式将Hoen博士的专业知识提升到一个新的水平：（1）通过提供她在开发，评估和应用生物医学信息学研究的新工具方面的指导研究经验； （2）通过为临床和转化研究提供生物医学信息学培训。 Hoen博士建议参加课程，研讨会，研讨会系列和研究会议，这些会议的重点是职业伦理学，翻译研究方法，计算生物学，包括基因组学，元基因组学，网络分析和系统生物学。 Hoen博士组建了一个由杰森·摩尔（Jason Moore）博士领导的示范指导团队，他拥有长期的指导，领导力和资助生物医学信息学研究的历史。她的导师和顾问团队包括有关信息学方法开发，网络分析和复杂系统的国际知名专家，元基因组数据，临床和转化科学的计算分析，流行病学和生物医学信息学领导。该团队体现的集体专业知识将为Hoen博士的职业发展以及成功执行其生物医学信息学转化研究的成功提供了出色的资源。 Hoen博士的团队致力于确保她在该奖项的时间范围内致力于独立时，取得了成功的研究和职业发展经验。 研究计划。拟议研究的目的是开发，评估和应用计算工具，以捕获微生物群落组成的大型纵向数据集，并结合从一项独特的大型分子流行病学研究中使用的丰富临床信息，使用一种系统方法，该方法着重于人类宿主之间的复杂相互作用，将细菌群体与疾病构成微生不足。构建这项研究的框架是一系列网络，这些网络代表婴儿与微生物定植模式之间的复杂相互作用，鉴于早期生活暴露和与健康相关的结果。提出的分析将解决这些网络捕获的复杂模式，包括多尺度关联，网络组件之间的多向交互以及变化网络中的时间动态。这项研究的总体假设是，这些创新的方法可以揭示微生物组组成与早期健康和疾病之间的关键关联。这项研究的转化潜力在于通过操纵和保留健康微生物组的疗法来降低疾病风险的新机会。