多序列比对:算法与应用

Osamu Gotoh
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引用次数: 102

摘要

阐明一个基因家族或基因产物的序列、结构、功能和进化(FESS关系)之间的相互关系是现代分子生物学的中心主题。多重序列比对已被证明是一个强大的工具等许多领域的研究系统发育重建、照明功能重要的地区,和预测蛋白质和rna的高阶结构。然而,从一组相关序列中自动构造多重比对是非常琐碎的。本文回顾了解决这一计算难题的各种方法。本文还讨论了多重对准在FESS关系解释中的几个重要应用。长期以来,渐进式方法一直是解决相当规模的多重对准问题的唯一实用手段。这种情况现在已经改变随着新技术的发展包括几类迭代方法。今天,多种序列比对方法的进展是由数学家、计算机科学家和包括生物物理学家在内的各个领域的生物学家的多学科努力取得的。这些想法也来自不同的背景,纯算法、统计学、热力学等等。这些成果现在受到生物科学许多领域的研究人员的欢迎。在不久的将来,广义多重对准可能会在FESS关系的研究中发挥核心作用。来自多个领域的知识的有组织的混合将会发酵,产生丰硕的成果,而这些成果在每个领域都很难获得。希望本文的综述能够为这一迅速发展的生物信息学领域的理论和实践的未来发展提供有益的信息资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple sequence alignment: Algorithms and applications

Elucidation of interrelationships among sequence, structure, function, and evolution (FESS relationships) of a family of genes or gene products is a central theme of modern molecular biology. Multiple sequence alignment has been proven to be a powerful tool for many fields of studies such as phylogenetic reconstruction, illumination of functionally important regions, and prediction of higher order structures of proteins and RNAs. However, it is far too trivial to automatically construct a multiple alignment from a set of related sequences. A variety of methods for solving this computationally difficult problem are reviewed. Several important applications of multiple alignment for elucidation of the FESS relationships are also discussed.

For a long period, progressive methods have been the only practical means to solve a multiple alignment problem of appreciable size. This situation is now changing with the development of new techniques including several classes of iterative methods. Today's progress in multiple sequence alignment methods has been made by the multidisciplinary endeavors of mathematicians, computer scientists, and biologists in various fields including biophysicists in particular. The ideas are also originated from various backgrounds, pure algorithmics, statistics, thermodynamics, and others. The outcomes are now enjoyed by researchers in many fields of biological sciences.

In the near future, generalized multiple alignment may play a central role in studies of FESS relationships. The organized mixture of knowledge from multiple fields will ferment to develop fruitful results which would be hard to obtain within each area. I hope this review provides a useful information resource for future development of theory and practice in this rapidly expanding area of bioinformatics.

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