Characterization, Quantification, and Management of Sequence-Alignment Errors with Emphasis on Molecular Phylogenetic Reconstructions

休斯顿大学获得了一项资助，用于描述和分类多序列比对中的错误，并设计工具和协议，通过这些工具和协议，可以解释和适当管理比对错误和不确定性。多序列比对是同源分子序列间进化和功能关系的最基本表征。它是几乎所有涉及序列比较的分析的起点，例如遗传距离的推导，同源位点的鉴定，系统发育重建，外显子，内含子和备选剪接位点的鉴定，以及从同源性预测蛋白质的三维结构。在系统发育重建的背景下，将特别注意多重比对误差的影响。校准误差管理的实际效果将在实际数据库和实际系统发育问题上进行评估。该项目将产生新的工具和协议，可用于改进许多工作假设所依据的数据。所有软件、数据和协议都将免费提供。该项目还将有助于培养研究生和本科生的科研能力，并鼓励每个学生参加科学会议，展示他们的发现。休斯敦大学是美国种族和民族最多样化的研究型大学之一，因此对学生的培训尤为重要。该项目的跨学科性质将促进我们实验室内外生物学家、计算机科学家、统计学家、数学家和物理学家之间的合作，这些互动将加强休斯顿大学数学和计算生物学的新兴研究生课程。

The University of Houston is awarded a grant to characterize and classify errors in multiple sequence alignment and to devise tools and protocols through which alignment errors and uncertainties can be accounted for and properly managed. Multiple sequence alignment is the most basic representation of evolutionary and functional relationships among homologous molecular sequences. It is the starting point of almost all analyses that involve sequence comparisons, such as derivation of genetic distances, identification of homologous sites, phylogenetic reconstruction, and identification of exons, introns, and alternative splicing sites, as well as prediction of three-dimensional structures of proteins from homology. Particular attention will be paid to the effects of multiple alignment errors in the context of phylogenetic reconstructions. The practical effects of alignment-error management will be assessed on real databases and real phylogenetic problems. This project will generate new tools and protocols that can be used to improve the data on which many working hypotheses are based. All software, data, and protocols will be made freely available. This project will also help in the training of graduate and undergraduate students in scientific research, and every student will be encouraged to attend scientific meetings to present their findings. The training of students at the University of Houston is particularly significant since UH is one of the most racially and ethnically diverse research campuses in the US. The inter-disciplinary nature of the project will promote collaborations within and outside our laboratory between biologists, computer scientists, statisticians, mathematicians, and physicists, and these interactions will strengthen an emerging graduate program in Mathematical and Computational Biology at the University of Houston.