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1、统计和计算遗传学国际研讨班第 二 轮 通 知一、研讨班概况多数生物性状尤其是对农林业生产重要的经济性状都是数量性状。数量性状遗传的复杂性给研究带来很大困难,而近年来基因组技术的发展为揭示数量性状遗传变异规律带来了极大帮助。高级基因组技术使得从分子水平上描述遗传多态现象成为可能,整个基因组数量遗传的性状得以鉴定,部分数量性状相关的基因也陆续被定位。随着大规模测序技术的发展和越来越多物种全基因组数据的获得,人们能够从基因组等水平更深入地认识物种、群体、家系和个体之间的数量性状的遗传变异,而统计分析则是分析基因组数据的重要工具。为了帮助遗传学家、统计学家和来自农林业、生物学、数学和统计学领域的研究生
2、和相关研究人员掌握基本的统计理论和最新的遗传数据分析方法和软件,了解相关领域的国际前沿,特邀请来自Pennsylvania State University等高海内外高校的统计和数量遗传学教授举办本届统计和计算遗传学国际研讨班。 本次研讨班由北京林业大学、中国林学会林木遗传育种分会和Pennsylvania State University共同主办,北京林业大学林木育种国家工程实验室、林木、花卉遗传育种教育部重点实验室和生物科学与技术学院承办。 二、主讲专家Dr. Rongling Wu (邬荣领), Pennsylvania State University (coordinator)Dr.
3、 Bailian Li (李百炼), North Carolina State University/Beijing Forestry University Dr. Arthur Berg, University of FloridaDr. Yuehua Cui, Michigan State UniversityDr. Tian Liu, Human Genetics Group at Genome Institute of Singapore三、主要形式和内容本次研讨班将采用专家讲座为主,讨论实际遗传数据的分析为辅的学习方式,还可根据需要对参会人员自带的数据和论文进行分析指导。研讨班讲座将
4、涵盖统计和计算遗传学的诸多领域,主要内容如下:(1) 群体遗传数据分析,包括遗传杂合度、连锁不平衡估计、多位点分析、多等位基因分析和合子的连锁不平衡等;(2) 数量性状位点(QTL)的遗传定位,包括分子标记和分离检验、连锁分析和作图、异交群体的连锁分析、单一标记分析、区间作图、二元性状的遗传作图、遗传印迹和eQTLs作图等;(3) 动态性状的功能定位,包括动态性状的种类、遗传作图的原理、依赖于时间的基因型值的参数模型、依赖于时间的基因型值的非参数模型、协方差结构的模型和遗传控制的时间模式的检验等;(4) 林木数量遗传学研究现状与最新进展。四、研讨班举办时间和地点1时间:2009年8月2日-8日
5、;2地点:北京海淀区王庄路18号西郊宾馆;3. 报到时间:2009年8月1日,上午8:30-下午5:30;4报到地点:北京海淀区王庄路18号西郊宾馆。五、乘车路线会议不安排接站,请自行前往。1北京站(距西郊宾馆约17公里):北京站乘地铁2号线(内环)- 西直门站下车 - 换乘地铁13号线- 五道口站下车 - 步行约10分钟至西郊宾馆。2北京西站(距西郊宾馆约16公里):北京西站 - 乘319路 - 清华园站下车- 换乘331路 - 北京语言大学站下车 - 步行约10分钟至西郊宾馆。3北京南站(距西郊宾馆约20公里):北京南站 - 乘特5路- 广安门内站下车 - 换乘743路 - 五道口站下车
6、- 步行约10分钟至西郊宾馆。4首都机场(距西郊宾馆约38公里):首都机场 - 乘机场巴士五线(首都机场-中关村)- 学院桥站 - 换乘375、331路 - 语言学院站下车 -步行约10分钟至西郊宾馆。六、费用标准注册费用2500元人民币(学生1500元,以学生证为准),含资料费、培训费等费用。 七、注意事项研讨班上会进行相关计算机程序的辅导,所以请大家自己携带个人电脑。欢迎广大遗传育种领域的研究人员、教师及研究生等报名参加,请于2009年7月25日前回复我们(纸版或电子版),我们将会及时和您联系。研讨班协调人:张志毅 教授, 邬荣领 教授联系人:郭允倩 电话:13810366698 E-ma
7、il: 庞晓明 电话:13681502814 E-mail: 通讯地址:北京林业大学118信箱(100083)传 真: 010623385028附件一:主讲专家简介Dr. Rongling Wu,With a rigorous training in genetics, Dr. Wu is fascinated by the mystery of how genes can generate such a vast amount of variation in nature and how mechanistic and developmental regulations guide gene
8、s to respond to environmental signals. Dr. Wus current research interest focuses on the development of statistical and computational methods necessary to unravel the genetic machinery of complex traits, diseases, and life processes. He is particularly interested in integrating the idea and principle
9、 of systems biology into statistical genetic research, ultimately elucidating a comprehensive atlas of the genetic control network of complex biology. He is alert and sensitive to concrete genetic or developmental problems fundamentally meaningful to agriculture, forestry, biology, and biomedicine a
10、nd exceptionally good at the design of statistical models and algorithms to solve these problems. His pioneering statistical work on functional mapping was highlighted in Nature Reviews Genetics in 2004 and 2006. Dr. Wu serves Associate Editor for a number of statistical and genetic journals.Dr. Bai
11、lian Li,Dr. Li is now Vice Provost for International Affairs of North Carolina State University (NCSU) and Yangtse River Scholar Professor of Beijing Forestry University. Dr Lis main research has focused on forest genetics, biotechnology, genomics and tree improvement. Previously, Dr. Li was a profe
12、ssor in the Department of Forestry and Environmental Resources and Co-Director of the NCSU Industry Tree Improvement Program. Dr. Li has extensive international experience in research and teaching collaboration with many foreign universities, research institutes and governmental agencies. He has bee
13、n active leader in several international profession organizations. Dr. Li serves as Associate Editor or Editor for a number of forestry and genetic journals, such as Forest Science, Canadian Journal of Forest Research and Annals of Forest Science etc.Dr. Auther Berg,Dr. Berg enjoys exploring the sci
14、ence of life, from genotypes to phenotypes, through a mathematical and statistical framework. With a strong background in statistical modeling and computation, Dr. Berg utilizes efficient statistical algorithms together with clustered processers to simultaneously analyze complex genetic and phenotyp
15、ic data. Outside of statistical genetics, Dr. Berg also performs methodological research in time series analysis, nonparametrics, survival analysis, and resampling methods. Before joining the faculty at the University of Florida, he held various other positions including associate-in instructor at t
16、he University of California, San Diego (UCSD) where he received a departmental teaching award, adjunct instructor at Miramar College, and administrative consultant of the Mathstorm consulting group at UCSD. He was recently presented with a 2008 Research Innovation Grant Award from the University of Florida for his research in s