MOLECULAR SEQUENCE DATA

分子序列数据

• 批准号: 3333456
• 负责人: SAMUEL KARLIN
• 金额: $ 40.64万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1988
• 资助国家: 美国
• 起止时间: 1988-08-01 至 1996-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3333456
• 关键词: DNA; biochemical evolution; computer assisted sequence analysis; computer program /software; computer simulation; genetic library; genome; mathematical model; nucleic acid sequence; protein folding; protein sequence; protein structure; statistics /biometry

The unprecedented accumulation of DNA and protein sequence (including the complete physical map of E. coli and the first complete nucleotide sequence of a eukaryotic chromosome (yeast chromosome III) poses challenges and opportunities in terms of organization and analysis. Our proposed research will focus on mathematical, statistical, computational, and informatics problems in this context. Main topics are (i) statistical theory and applications of score-based sequence analysis; (ii) theory and applications of rho- scan statistics for heterogeneity assessments within and among sequences; (iii) development of computer programs for the statistical analysis of protein and nucleotide sequences (SAPS and SANS); (iv) studies on oligonucleotides compositional biases including characterizations of rare and frequent oligonucleotides; (v) definitions and applications of distance measures and orderings among DNA sequences. Score-based sequence analysis methods are in wide use, both with respect to single sequences (e.g., hydropathy plots) and with respect to sequence comparisons (e.g. BLAST). Relevant probability distributions approximations will be derived for sums of high scoring segments, the maximal matching alignment score in the case that scores are random vectors (representing, for example, simultaneously charge, hydrophobicity, and steric attributes of an amino acid). Computer algorithms will be devised to calculate approximate probabilities for given sets of parameters. Rho-scans assess anomalies in the distribution of markers along a line (e.g. restriction sites, special oligonucleotides, nucleosome placements). The theory will be developed to accommodate deviations from a specified theoretical distribution and for data comparisons among several sequences. These programs will implement in addition to above methods a large number of other statistics (e.g., compositional evaluations with multivariate quantile distributions; counts and spacings of close repeats and close dyads) and should help with the design of experiments. Methods for evaluating oligonucleotide compositional biases and distance measures based on oligonucleotide composition are proposed to assess differences and similarities among and within sequences, with particular relevance to functional/structural roles and phylogenetic reconstructions. Intensive detailed studies on large genomic sequences will be conducted for comparative purposes and to identify special regions (origin of replications, regulatory sequences, and structural elements).

DNA和蛋白质序列的前所未有的积累（包括 大肠杆菌的完整物理图和第一个完整的核苷酸 真核染色体（酵母染色体III）的序列姿势 关于组织和分析的挑战和机遇。 我们的 拟议的研究将侧重于数学，统计，计算， 在这种情况下的信息问题。 主要主题是（i） 统计理论和基于分数序列分析的应用； （ii）罗扫描统计的异质性的理论和应用 序列内外的评估； （iii）计算机的开发 蛋白质和核苷酸序列统计分析的程序 （SAPS和SANS）； （iv）寡核苷酸组成偏见的研究 包括稀有和频繁的寡核苷酸的特征； （v） DNA之间距离测量和顺序的定义和应用 序列。 基于分数的序列分析方法广泛使用，两者都 关于单个序列（例如，水上图），并与 尊重序列比较（例如爆炸）。 相关概率 分布近似值将得出高分的总和 细分市场，最大匹配对准得分在得分的情况下 是随机向量（例如代表同时充电， 疏水性和氨基酸的空间属性）。 电脑 将设计算法来计算近似概率 给定的一组参数。 Rho-Scans评估分布的异常 沿线的标记物（例如限制站点，特殊 寡核苷酸，核小体位置）。 理论将发展 为了适应特定理论分布的偏差和 用于几个序列之间的数据比较。 这些程序将 除上述方法外，实施了大量其他统计数据 （例如，具有多元分位数的组成评估 分布；重复重复和近二元的计数和间距）和 应该有助于设计实验。 评估方法 基于寡核苷酸的组成偏差和距离测量 提出了寡核苷酸组成来评估差异和 序列之间和内部的相似性，与 功能/结构作用和系统发育重建。 密集的 将对大型基因组序列进行详细研究 比较目的并确定特殊区域（起源于 复制，调节序列和结构元素）。