CAREER: New Technologies for Biosequence Comparison

生物序列的计算比较是现代生物学的基础。这是对新测序基因组的功能元件进行注释的最快、使用最广泛的技术。用于比较的算法必须解决序列数据库大小的快速增加和对更灵敏的多比对工具的需要，以及比较推断的特征模型的需要。增强构成快速比较工具核心的模式匹配算法是本研究的重点。将纳入合理模式设计的研究框架和将模式匹配与替换分数矩阵相结合的技术。模式匹配概括了对齐算法的词匹配启发式算法。模式的选择会影响搜索的速度和灵敏度。改进的搜索模式将专用于特定的特征类型，例如编码序列或生物体组。与流行的搜索工具开发商建立了合作关系，这将有助于整合新的方法。研究培训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.