Statistical Mechanics of Sequence Matching

9971456 Hwa这是一个新的赠款共同资助的材料研究和分子和细胞生物学的部门与数学和物理科学的多学科活动办公室的董事会。 本理论计画将应用统计力学与非平衡态动力学的方法，来阐明DNA与蛋白质序列配对问题的统计与相图。 在最近的一系列研究中，已经发现广泛使用的序列比对算法，例如，Smith-Waterman算法类似于统计物理学中的一些常见问题，即随机相关介质中有向路径的钉扎，以及噪声环境中生长表面的非平衡粗糙化。 这种类比表明了一种与当前计算生物学所采用的方法截然不同的序列比对方法。 将开发新的分析方法来计算随机和相互关联序列排列的相图的近似形式和各种特征尺度的大小。 由于序列相关性引起的相图中的移位将用于精确定位用于检测同源序列的最佳参数方案。 此外，将使用经验方法从单个序列对的比对中快速提取罕见事件统计数据（而不是从集合中收集统计数据，比如通过序列的随机重排）。 这种方法应该导致有效地确定每个比对的统计显著性。随后通过改变评分参数来优化该显著性值应产生对弱序列同源性敏感的所需高保真比对。 扩展现有的算法，考虑到长范围内的序列相关性，长段的插入/删除，和多个地区的近最佳匹配也将进行研究。 最后，正在开发的序列比对的概念方法和数学方法也可以应用于理解长DNA分子的物理关联。 后者提出了一些新的问题，统计力学是有趣的研究在自己的权利。 本学科为新一代跨学科物理学家提供了一个很好的训练基地，他们将学习和应用现代统计力学的复杂方法，同时欣赏和发现分子生物学中有趣的当前问题。这是一项新的赠款，由材料研究和分子与细胞生物学部门与数学和物理科学多学科活动办公室共同资助。 本理论计画将应用统计力学与非平衡态动力学的方法，来阐明DNA与蛋白质序列配对问题的统计与相图。该补助金为新一代跨学科物理学家提供了一个很好的培训基地，他们将学习和应用现代统计力学的复杂方法，同时欣赏和发现分子生物学中有趣的当前问题。

9971456HwaThis is a new grant funded jointly by the Divisions of Materials Research and Molecular and Cellular Biology with the Directorate of Mathematical and Physical Science's Office of Multidisciplinary Activities. This theoretical project will apply the methods of statistical mechanics and nonequilibrium dynamics to elucidate the statistics and phase diagram of DNA and protein sequence matching problems. In a series of recent studies it has been found that the widely used sequence alignment algorithms, e.g., the Smith-Waterman algorithm, are analogous to some familiar problems in statistical physics, namely, the pinning of a directed path in random and correlated media, and the nonequilibrium roughening of growing surfaces in a noisy environment. This analogy suggests an approach to sequence alignment that is very different from the current one taken in computational biology. New analytical methods will be developed to calculate the approximate form of the phase diagram and the magnitude of various charcteristic scales for the alignment of random and mutually correlated sequences. The shift in phase diagram due to sequence correlations will be used to pinpoint the optimal parameter regime for detecting homologous sequences. Also, an empirical method will be used to extract the rare-event statistics quickly from the alignment of individual sequence pairs (rather than collecting statistics from an ensemble, say, via the random shuffling of sequences). This method should lead to efficient determination of the statistical significance of each alignment. Subsequent optimization of this significance value by varying score parameters should then yield the desired high-fidelity alignment sensitive to weak sequence homologies. Extension of existing algorithms to take into account long-range intra-sequence correlations, long segments of insertion/deletions, and multiple regions of near-optimal matchings will also be studied. Lastly, the conceptual approach and mathematical methods being developed for sequence alignment can also be applied to understand the physical association of long DNA molecules. The latter suggests a number of novel problems of statistical mechanics which are interesting to study in their own right. This subject provides an excellent training ground for a new generation of interdisciplinary physicists, who will learn and apply the sophisticated methods of modern statistical mechanics, and at the same time, appreciate and discover interesting current problems in molecular biology. This is a new grant funded jointly by the Divisions of Materials Research and Molecular and Cellular Biology with the Directorate of Mathematical and Physical Science's Office of Multidisciplinary Activities. This theoretical project will apply the methods of statistical mechanics and nonequilibrium dynamics to elucidate the statistics and phase diagram of DNA and protein sequence matching problems. The grant provides an excellent training ground for a new generation of interdisciplinary physicists, who will learn and apply the sophisticated methods of modern statistical mechanics, and at the same time, appreciate and discover interesting current problems in molecular biology.