CAREER: New Technologies for Biosequence Comparison

生物序列的计算比较是现代生物学的基础。它是对新测序基因组的功能元素进行注释的最快、最广泛使用的技术。比较算法必须解决序列数据库规模快速增长的问题，需要更灵敏的多比对工具，以及比较推断特征模型的需要。增强模式匹配算法是快速比较工具的核心，是本研究的重点。本文将引入理性模式设计的研究框架和模式匹配与替代得分矩阵相结合的技术。模式匹配推广了对齐算法的词匹配启发式。模式的选择会影响搜索的速度和灵敏度。改进后的搜索模式将专门针对特定的特征类型，如编码序列或生物体群。与流行的搜索工具开发人员建立了合作关系，这将有助于整合新方法。研究训练涉及多个层次的学生，也将构成跨学科学生交流的基础。

Computational comparison of biosequences is fundamental to modern biology. It is the fastest, most widely used technology to annotate the functional elements of a newly sequenced genome. Algorithms for comparison must address the rapid increase in the size of sequence databases and the need for more sensitive tools of multiple alignments, as well as the need to compare inferred feature models. Enhancing the pattern-matching algorithms that form the heart of fast comparison tools is the focus of this research. A research framework for rational pattern design and a technique for combining pattern matching with substitution score matrices will be incorporated. Pattern matching generalizes the word-matching heuristics of alignment algorithms. The choice of pattern can impact the search speed and sensitivity. The improved search patterns will be specialized to particular feature types, such as coding sequence, or to groups of organisms. Collaborations with popular search tool developers are established and will help integrate the new methods. Research training involves students at many levels and will also form the basis of cross-disciplinary student exchanges.