STATISTICAL ANALYSIS OF LONG DNA SEQUENCES

基因组序列的快速积累增加了对 破译数据库中收集的遗传信息的方法，如 GenBank。虽然有许多方法可以彻底分析小分子物质 在过去已经开发了序列，但仍然缺乏 用于大型DNA序列宏观分析的强大程序。组合 统计分析和现代计算机能力使搜索成为可能 对于长序列中的诊断模式具有高速，并且 评估它们之间的相同点和不同点，以便更好地恢复 隐藏在这些有机分子中的生化信息。 拟议研究的目标是开发新的方法 计算机化统计分析，并同时应用于分析 可利用的大基因组序列，如医学上的基因组 重要的疱疹病毒家族。 这些方法的目的是识别生物活性部位(例如 起源、复制和核小体定位信号)。预期中的 该方法基于对长DNA字母序列的自动扫描 找出序列之间的相似或不同之处，例如通过使用 二核苷酸距离测量。概率标准(如r-扫描和 光谱包络)将应用于所有可能检测到的站点 生物学兴趣，从中挑选出最有可能的候选者。 这个项目寻求实验和理论之间的密切合作。 科学家，即病毒学家和数学家。跨学科 方法确保理论工作与当前的生物医学相联系 问题和新开发的方法立即得到应用。

Rapid accumulation of genomic sequences has increased the demand for methods to decipher the genetic information gathered in data banks such as GenBank. While many methods for a thorough micro-analysis of small sequences have been developed in the past, there is still a shortage of powerful procedures for macro-analyses of large DNA sequences. Combining statistical analysis and modern computer power makes it feasible to search with high speed for diagnostic patterns within long sequences and to evaluate similarities and differences between them in order to recover much of the biochemical information hidden in these organic molecules. The objectives of the proposed study are to develop novel methods of computerized statistical analysis and simultaneously apply them to analyze available large genomic sequences, as the genomes of the medically important herpesvirus family. The methods aim at the identification of biologically active sites (e.g. origins replication, and nucleosome positioning signals). The anticipated approach is based on an automated scanning of long DNA letter sequences and to find similarities or differences between sequences, e.g., by using dinucleotide distance measures. Probabilistic criteria (as r-scan and spectral envelopes) will be applied to all detected sites of possible biological interest to sort out the most likely candidates among them. This project seeks close collaboration between experimental and theoretical scientists, namely virologists and mathematicians. The interdisciplinary approach ensures that the theoretical work is linked to current biomedical problems and that newly developed methods are immediately applied.