Conferences on Emerging Statistical Issues in Biomedical Research

描述(申请人提供)：这是R13申请的更新，以继续非常成功的关于健康科学中基因组研究中新出现的统计和量化问题的年度会议系列，该会议由哈佛大学公共卫生学院(HSPH)定量基因组学(PQG)计划在过去五年中主办，并向整个研究界开放。现代健康科学正在迅速发展，这在很大程度上是由高通量生物技术的快速发展推动的。这种不断变化的格局为健康科学的研究人员，特别是癌症和其他慢性疾病的研究人员提供了利用遗传信息进行新发现的丰富机会，以更好地了解疾病生物学和病因学以及基因和环境的相互作用，并在患者护理中加强风险预测和个性化医学。虽然这样的“组学”时代提供了许多令人兴奋的研究机会，但关于人类基因组的海量信息的爆炸性增长在数据处理、集成、分析和结果解释方面提出了非凡的挑战。传统的统计和计算技术不能满足这些新的要求。迫切需要在科学探索的前沿讨论新出现的量化问题，并促进创新的统计和定量方法的发展，以处理基础、人口和临床科学中的海量高通量基因组和组学数据。在这次续订申请中，我们建议继续主办这一系列会议，每个会议都集中在当前基因组研究感兴趣的新兴量化研究领域，特别的重点将随着时间的推移而演变。会议系列的一个主要特点是提供一个及时和互动的平台，让跨学科的高级和初级研究人员，如统计遗传学家、计算生物学家、遗传流行病学家、分子生物学家和癌症和其他慢性疾病的临床科学家，批评现有的定量方法，深入讨论新出现的统计和定量问题，确定未来研究的优先事项并传播结果。2011年的会议题为“基因组医学中新出现的统计和量化问题”。2012年的会议主题是“超越1000个基因组计划：测序、复杂特征和种群”。该系列会议由HSPH PQG、HSPH的生物统计部和Dana Farber癌症研究所的生物静力学和计算生物学系共同主办。将继续作出认真努力，让初级研究人员、妇女和少数群体参与会议活动。 公共卫生相关性：关于人类基因组的海量信息的爆炸性增长在数据处理、集成、分析和结果解释方面提出了非同寻常的挑战。提议召开一次关于健康科学基因组研究中新出现的统计和数量问题的年度会议，以继续让跨学科的定量和专题研究人员批评现有的定量方法，深入讨论新出现的统计和数量问题，确定未来研究的优先事项，并传播健康科学基因组研究的成果。

DESCRIPTION (provided by applicant): This is a renewal of the R13 application to continue the very successful annual conference series on Emerging Statistical and Quantitative Issues in Genomic Research in Health Sciences, which has been hosted by the Program in Quantitative Genomics (PQG) at Harvard School of Public Health (HSPH) in the last five years and is open to the whole research community. Modern health sciences are evolving rapidly, driven in large part by the rapid advance of high- throughput biotechnology. This changing landscape has provided researchers in health sciences, especially in cancer and other chronic diseases, with rich opportunities for new discoveries using genetic information to better understand disease biology and etiology and interplay of genes and environment, and to enhance risk prediction and personalized medicine in patient care. While such an "omics" era presents many exciting research opportunities, the explosion of massive information about the human genome presents extraordinary challenges in data processing, integration, analysis and result interpretation. Traditional statistical and computational techniques cannot meet these new demands. There is a critical need to discuss emerging quantitative issues at the forefront of scientific exploration, and to promote development of innovative statistical and quantitative methods to deal with massive high- throughput genomic and 'omics data in basic, population and clinical sciences. In this renewal application, we propose to continue hosting this conference series, where each conference focuses on emerging quantitative research areas of most current genomic research interest and the particular focus will evolve over time. A key feature of the conference series is to provide a timely and interactive platform to engage cross-discipline senior and junior investigators, such as statistical genetists, computational biologists, genetic epidemiologists, molecular biologists, and clinical scientists in cancer and other chronic diseases to critique existing quantitative methods, discuss in-depth emerging statistical and quantitative issues, identify priorities for future research and disseminate results. The 2011 conference is entitled ''Emerging Statistical and Quantitative Issues in Genomic Medicine." The 2012 conference is on " Beyond the 1000 Genomes Project: Sequencing, Complex Traits, and Population." The Conference series is cosponsored by HSPH PQG, the Department of Biostatistics of the HSPH and the Department of Biostatics and Computational Biology of the Dana Farber Cancer Institute. Serious efforts will continue to engage junior researchers, women and minorities in Conference activities. PUBLIC HEALTH RELEVANCE: The explosion of massive information about the human genome presents extraordinary challenges in data processing, integration, analysis and result interpretation. An annual conference on Emerging Statistical and Quantitative Issues in Genomic Research in Health Sciences is proposed to continue engaging cross-disciplinary quantitative and subject-matter researchers to critique existing quantitative methods, discuss in-depth emerging statistical and quantitative issues, identify priorities for future research and disseminate results in genomic research in health sciences.