CAREER: New Technologies for Biosequence Comparison

生物序列的计算比较是现代生物学的基础。 它是最快，最广泛使用的技术来注释新测序的基因组的功能元件。 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重比对工具的需求，以及对比较推断的特征模型的需求。 加强模式匹配算法，形成快速比较工具的心脏是这项研究的重点。 一个合理的模式设计的研究框架和技术相结合的模式匹配与替代得分矩阵将被纳入。 模式匹配推广了对齐算法中的词匹配算法。 模式的选择会影响搜索速度和灵敏度。 改进的搜索模式将专门用于特定的特征类型，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，这将有助于整合新方法。 研究培训涉及许多层次的学生，也将形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.