Tissue-specific gene set testing

组织特异性基因组测试

• 批准号: 9217355
• 负责人: Hildreth Frost
• 金额: $ 8.69万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9217355
• 关键词: Academic Training; Address; Atlases; Bioinformatics; Biological; Biometry; Cataloging; Catalogs; Code; Collection; Consult; Core Facility; DNA Methylation; DNA Sequence; Data; Data Science; Databases; Development; Development Plans; Education; Educational workshop; Environment; Evaluation; Exposure to; Faculty; Generic Drugs; Genes; Genetic Transcription; Genomics; Grant; Histocompatibility Testing; Human; Individual; Investigation; Knowledge; Lead; Leadership; Link; Measures; Medical Informatics; Medicine; Mentors; Methods; Molecular Profiling; Ontology; Pathway Analysis; Performance; Process; Productivity; Proteins; Qualifying; Reproducibility; Research; Research Infrastructure; Research Project Grants; Research Training; Resources; Source; Specificity; Supercomputing; Test Result; Testing; Tissues; Training; Translational Research; Tweens; Variant; Writing; biomedical informatics; career; career development; computerized tools; experience; gene function; genomic data; human tissue; improved; medical schools; member; novel; repository; research and development; research study; symposium; tool

PROJECT SUMMARY Background: Gene set testing, or pathway analysis, has become a critical tool for the analysis of high- dimensional genomic data. Although the function of many genes is strongly linked to tissue context, with recent experiments characterizing the tissue-specificity of most human protein-coding genes, little support is available for tissue-specific gene set testing. An important opportunity therefore exists to create novel bioinformatics methods that use the comprehensive data on the tissue-specificity of human genes to create tissue-specific gene set collections, annotations and testing methods. Candidate: Dr. Frost is a faculty member in the Department of Biomedical Data Science at the Geisel School of Medicine at Dartmouth. His academic training at Stanford, Harvard and Dartmouth, strong record of research productivity and extensive medical informatics consulting experience make him well qualified to achieve his proposed career and research aims and transition to research independence. Environment: The Geisel School of Medicine at Dartmouth is an optimal environment for Dr. Frost's career development and research. Dr. Frost's team of experienced mentors and advisors, along with a wide network of other collaborating faculty, will provide a supportive and invigorating intellectual en- vironment. Numerous core facilities, including a state-of-the-art supercomputing cluster, will provide the necessary technical infrastructure and regular seminars, grand rounds and workshops will provide exposure to recent advances in topics including biomedical informatics, biostatistics and genomics. Career Development Plan: The proposed career development plan will achieve the three primary aims of 1) biomedical expertise, 2) training for research leadership and 3) research independence through a combination of scientific education, career development and mentored research. All of these activities will be guided by Dr. Frost's mentoring and advising team, lead by Dr. Christopher Amos. To achieve the first aim, Dr. Frost will improve his biomedical domain knowledge, focusing on genomics and ge- nomic medicine, through classes, workshops, short courses, seminars and conferences. To achieve the second aim, Dr. Frost will pursue training in translational science, the responsible conduct of research and grant writing. The third aim will be realized through the development of a competitive R01 grant. Research Plan: Dr. Frost will address the challenge of tissue-specific gene set testing by developing and evaluating bioinformatics methods that leverage information on tissue-specific gene function to create gene set collections and testing methods that target a single human tissue type. These methods will 1) filter out gene sets not relevant to the tissue, 2) eliminate gene set annotations inappropriate for the tissue, and 3) leverage tissue-specific gene relationships to improve gene set enrichment.

项目摘要 背景：基因组检测，或途径分析，已成为分析高风险的重要工具。 三维基因组数据。尽管许多基因的功能与组织环境密切相关， 随着最近的实验描述了大多数人类蛋白质编码基因的组织特异性， 支持组织特异性基因集测试。因此，存在一个重要的机会， 创建新的生物信息学方法，使用组织特异性的综合数据， 人类基因的基因组，以创建组织特异性基因集集合，注释和测试方法。 候选人：Frost博士是Geisel生物医学数据科学系的教员 达特茅斯医学院。他在斯坦福大学、哈佛和达特茅斯的学术训练， 研究生产力的记录和广泛的医学信息咨询经验使他很好 有资格实现他提出的职业和研究目标，并过渡到研究独立。 环境：达特茅斯的盖泽尔医学院是弗罗斯特博士的最佳环境。 职业发展和研究。弗罗斯特博士的团队经验丰富的导师和顾问，沿着， 其他合作教师的广泛网络，将提供一个支持和振兴智力en- - 谢谢众多的核心设施，包括最先进的超级计算集群，将提供 必要的技术基础设施和定期研讨会、大型圆桌会议和讲习班将提供 接触最新进展的主题，包括生物医学信息学，生物统计学和基因组学。 职业发展计划：拟议的职业发展计划将实现三个主要目标 1）生物医学专业知识，2）研究领导能力的培训和3）研究独立性，通过 科学教育，职业发展和指导研究相结合。所有这些活动 将由弗罗斯特博士的指导和咨询团队指导，由克里斯托弗·阿莫斯博士领导。实现 第一个目标，弗罗斯特博士将提高他的生物医学领域的知识，专注于基因组学和基因工程， 通过课程、讲习班、短期课程、研讨会和会议，开展营养医学。实现 第二个目标，弗罗斯特博士将继续在转化科学，负责任的研究行为的培训 并授予写作。第三个目标将通过发展竞争性R 01赠款来实现。 研究计划：Frost博士将通过开发组织特异性基因集测试来解决这一挑战。 评估生物信息学方法，利用组织特异性基因功能的信息， 创建针对单一人体组织类型的基因集集合和测试方法。这些方法 将1）过滤掉与组织不相关的基因组，2）消除不适合于 组织，以及3）利用组织特异性基因关系来改善基因集富集。