Statistics Of Sequence Comparison

这个项目是对一些问题的持续研究，这些问题是关于当比较两个蛋白质或DNA序列时，预计会出现哪些纯粹偶然的相似之处。一个附属的和相关的问题涉及到评分系统的定义，该评分系统是区分具有生物意义的模式和偶然性相似之处的最佳方式。今年的工作包括：a)调查基于块的评分系统的统计数据--在某些参数范围内，最佳基于块的分数的分布被发现由极值分布合理地很好地模拟。在识别遥远的生物关系方面，这种分数是否比蛋白质“轮廓”或特定位置的分数矩阵更敏感仍有待确定；b)对“混合”局部比对评分系统的统计数据的初步调查--该方法被发现产生的分数遵循具有可预测的尺度参数lambda的极值分布。

This project is a continuing study of questions concerning what similarities can be expected to occur purely by chance when two protein or DNA sequences are compared. A subsidiary and related question concerns the definition of scoring systems that are optimal for distinguishing biologically meaningful patterns from chance similarities. Work this year includes: a) Investigation of the statistics of a block-based scoring system - within certain parameter ranges, the distribution of optimal block-based scores was found to be reasonably well modelled by an extreme value distribution. Whether such scores are more sensitive in recognizing distant biological relationships than protein "profiles" or position-specific score matrices remains to be determined; b) Initial investigation of the statistics of the "hybrid" local alignment scoring system - this method was found to produce scores that follow an extreme value distribution with predictible scale parameter lambda.