THEORY AND APPLIED STUDIES IN EVOLUTIONARY GENETICS

描述：塞缪尔·卡林博士请求为一个为期5年的项目提供资金 进行数学、统计和计算方面的研究 分子进化和系统发育。三个主要研究领域有 已被确认身份。 第一个领域涉及统计方法的发展 分析整个基因组。卡林博士提出了一些两两配对的 基于二、三、四元组分相对丰度的距离度量 或更高阶的寡核苷酸序列。这些措施不需要 必然表现出可加性或满足三角不等式，但可以 根据两个序列的相对距离进行排序 第三个，标准序列。在之前的工作中，卡林博士和他的 合伙人开发了一种使用这种偏序的方法来 重建系统发展史。拟议的研究将继续发展 基于部分序列的无对齐距离度量和系统发育 并将使用可用的数据库测试这些方法。 第二，蛋白质序列之间的系统发育关系将是 检查并与基因组比较的结果进行比较。Dr。 卡林和他的同事们最近发展了一种分析理论 用于识别比对序列中具有统计意义的同源性。 对于给定的序列对，对应的序列之间的相似性 每个部位的氨基酸都会根据生化或 经验性信息。卡林发展的统计理论 小组确定了蛋白质中显示出显著意义的区域 相似之处。建议的工作将应用这种方法来估计 蛋白质之间的系统发育关系，仅限于考虑 显示出显著同源性的区域。蛋白质序列可用于 将对各种各样的生物进行分析和系统发育 利用偏序方法开发的重构。 将特别研究复制和转录因子。 研究的第三个主要焦点涉及分析共享和 蛋白质的不同特征。在上一个资助期内， 主要的工作是发展统计和计算 SAPS中实施的工具(蛋白质序列的统计分析) 包裹。SAPS软件可识别特定氨基酸的特性 也显示出统计上显著不同的酸序列 与一组参考蛋白质的相似性。已检查的属性 包括氨基酸组成、电荷分布、聚集或 氨基酸种类的分散，以及重复结构。SAPS 软件将被用来分析广泛的蛋白质家族。 需要解决的问题之一是确定哪些类型 在序列之间共享或不同的特征。例如, 表达所必需的特征应该跨物种保存， 虽然特定功能的特征应该有所不同 按函数划分的子群；此外，基本上不受约束的区域 应该表现出随机的发散。SAPS软件旨在 识别在统计上有显著相似性的区域 不同之处。

DESCRIPTION: Dr. Samuel Karlin requests funds for a 5-year project to conduct mathematical, statistical, and computational studies in molecular evolution and phylogenetics. Three major research areas have been identified. The first area addresses the development of statistical methodologies for analyzing whole genomes. Dr. Karlin has proposed a number of pairwise distance measures based on the relative abundances of di-, tri-, tetra- or higher-order oligonucleotide sequences. These measures need not necessarily show additivity or satisfy the triangle inequality, but can be ordered according to the relative distances of the two sequences to a third, standard sequence. In previous work, Dr. Karlin and his associates developed a method for using such partial orderings to reconstruct phylogenies. Proposed studies will pursue the development of alignment-free distance measures and phylogenies based on partial orderings, and will test these methods using available databanks. Second, phylogenetic relationships among protein sequences will be examined and compared to the results of the genomic comparisons. Dr. Karlin and his associates have recently developed an analytical theory for recognizing statistically significant homology in aligned sequences. For a given pair of sequences, the similarity between the corresponding amino acids at each site is assigned a score based on biochemical or empirical information. The statistical theory developed by the Karlin group identifies regions of the proteins that show significant similarity. The proposed work will apply this approach to estimate phylogenetic relationships among proteins, restricting consideration to regions showing significant homology. Protein sequences available for a wide variety of organisms will be analyzed and phylogenies reconstructions developed using the method of partial orderings. Replication and transcription factors in particular will be studied. The third primary focus of research involves the analysis of shared and diverged features of proteins. During the preceding funding period a major effort was the development of the statistical and computational tools implemented in the SAPS (Statistical Analysis of Protein Sequences) package. The SAPS software identifies characteristics of a given amino acid sequence that show statistically significant dissimilarity as well as similarity to a reference set of proteins. Attributes examined include amino acid composition, charge distribution, clustering or dispersion of types of amino acids, and repetitive structures. The SAPS software will be used to analyze a wide range of protein families. Among the questions to be addressed is the determination of the kinds of features that are shared or diverged among sequences. For example, features essential for expression should be conserved across species, while features characteristic of specific functions should differ across subgroups partitioned by function; further, largely unconstrained regions should show random divergence. The SAPS software is designed to recognize regions of statistically significant similarity and dissimilarity.