Statistics Of Sequence Comparison

序列比较统计

• 批准号: 7148022
• 负责人: STEPHEN F ALTSCHUL
• 金额: --
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7148022
• 关键词: bioinformatics; computational biology; computer assisted sequence analysis; molecular biology information system; nucleic acid sequence; protein sequence; statistics /biometry; thermodynamics

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 has focussed on two area. First, we have continued development and implementation of a method to transform an amino acid substitution matrix for use in the comparison of proteins having non-standard amino acid compositions. We have described in detail and implemented a numerical procedure for accomplishing this transformation. The transformation may leave the matrix's relative entropy unconstrained, or it may constrain it to equal a specified value. We have investigated experimentally which approach is best for producing matrices that are sensitive for general purpose database searches. We have found that constraining matrices to have relative entropy near 0.44 nats on average yields the best results. Second, we have studied "standard" and "composition based" statistics for the translated nucleic-acid database search program tblastn. In general, statistics based on standard amino acid compositions yield extremely unreliable E-values, which frequently claim chance alignments to be highly statistically significant. By estimating the "composition" of a database sequence from a window surrounding any given alignment, we are able to scale the substitution matrix so that it yields accurate "composition based" E-values. This procedure has now been implemented in NCBI's version of tblastn.

这个项目是一个持续的研究问题，关于什么相似之处可以预期 当比较两个蛋白质或DNA序列时，一个附属的和相关的问题涉及到评分系统的定义， 有生物学意义的模式。今年的工作重点是 两个地区。 首先，我们继续开发和实施一种方法， 用于比较具有非标准氨基酸的蛋白质的酸取代矩阵 酸组合物。我们已经详细描述并实现了一个数值过程， 完成这一转变。变换可能会留下矩阵的相对熵 不受约束，也可以将其约束为等于指定值。我们已经调查 实验上，哪种方法最适合于产生对一般情况敏感的基质 目的数据库搜索。我们已经发现，约束矩阵具有相对熵 平均接近0.44NAT产生最佳结果。 其次，我们研究了翻译作品的“标准”和“基于成分”的统计数据， 核酸数据库搜索程序tblaetry。一般来说，基于标准氨基酸的统计数据 酸的组成产生极不可靠的E值，它经常声称偶然排列 在统计学上非常重要。通过估计数据库序列的“组成”， 从围绕任何给定比对的窗口，我们能够缩放替换矩阵， 它产生精确的“基于成分的”E值。这一程序现已实施 在NCBI版的tblaetum中