Modelling and Analysis of Gene Duplication

基因复制是进化背后的驱动力，是进化生物信息学的中心课题。基因复制建模和分析项目将考虑（一）基因复制的生物学建模，包括基因的出生和死亡过程，以及影响重复基因保留的过程，以及（二）保留的基因重复数据的统计建模。此外，它还将解决两种模型的结合，以便可以对生物学机制的各个方面作出推断。这个项目的大背景是提供更好的基因树模型，作为基因和物种树协调问题的一部分。测量误差的统计模型问题、不同来源的数据合并以及对树木数据的分析也将在实际出现时加以处理。PI将培训和指导研究生和博士后在基因复制数据分析中出现的统计建模和实践。这种分析所需的技术技能和方法可以转移到生物信息学和其他数据丰富领域的更大领域的其他应用中。该项目还将在向更多的受众传播统计资料，特别是生物学方面的统计资料方面产生更广泛的影响。听众将包括从怀俄明大学科学和数学教学中心获得专业发展的K-12教师，怀俄明州科学博览会的参与者，怀俄明大学的学生以及大学周围更大社区的成员，他们可以参与当前生物/医学主题的统计问题的公开讨论。其他学生群体，如怀俄明大学“女性参与科学会议”的初中和高中参与者，以及怀俄明大学正在进行的暑期生物信息学项目的本科生参与者，也将作为该项目的一部分纳入互动。

Gene duplication is the driving force behind evolution, and it is a central topic in evolutionary bioinformatics. The project on modeling and analysis of gene duplication will consider (i) biological modeling of gene duplication, including processes for the birth and death of genes, and processes affecting the retention of duplicate genes, and (ii) statistical modeling of the data on retained gene duplicates. In addition, it will also address the incorporation of both models so that inference can be made about aspects of the biological mechanisms. The larger context for this project is to provide better modeling of gene trees as part of the gene and species trees reconciliation problem. Statistical modeling issues of measurement error, incorporation of data from different sources, and the analysis of data on trees will also be addressed as they arise practically.The PI will train and mentor graduate students and a post-doc in statistical modeling and practice as it arises in the analysis of gene duplication data. Technical skills and methodology needed for this analysis can be transferred to other applications in the larger area of bioinformatics and other data-rich fields. The project will also have broader impacts in the communication of statistical information, especially in a biological context, to a larger audience. The audience will include K-12 teachers who obtain professional development from the Science and Math Teaching Center at the University of Wyoming, participants in the Wyoming State Science Fair, students at the University of Wyoming and members of the larger community surrounding the university who can participate in public discussions of statistical issues in current biological/medical topics in the news. Other student populations such as junior high and high school participants in the Women in Science conferences at the University of Wyoming and undergraduate participants in the ongoing summer Bioinformatics program at the University of Wyoming will also be included in interactions as part of this project.