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关于分子生物学中的一些优化问题。

On some optimization problems in molecular biology.

作者信息

Festa P

机构信息

Department of Mathematics and Applications, University of Napoli FEDERICO II, Napoli, Italy.

出版信息

Math Biosci. 2007 Jun;207(2):219-34. doi: 10.1016/j.mbs.2006.11.012. Epub 2007 Feb 8.

Abstract

In the last two decades, the study of gene structure and function and molecular genetics have become some of the most prominent sub-fields of molecular biology. Computational molecular biology has emerged as one of the most exciting interdisciplinary fields, riding on the success of the ongoing Human Genome Project, which culminated in the 2001 announcement of the complete sequencing of the human genome. The field has currently benefited from concepts and theoretical results obtained by different scientific research communities, including genetics, biochemistry, and computer science. It is only in the past few years that it has been shown that a large number of molecular biology problems can be formulated as combinatorial optimization problems, including sequence alignment problems, genome rearrangement problems, string selection and comparison problems, and protein structure prediction and recognition. This paper provides a detailed description of some among the most interesting molecular biology problems that can be formulated as combinatorial optimization problems and proposes a new heuristic to find improved solutions for a particular class of them, known as the far from most string problem.

摘要

在过去二十年中,基因结构与功能研究以及分子遗传学已成为分子生物学中一些最为突出的子领域。随着正在进行的人类基因组计划取得成功,计算分子生物学应运而生,成为最令人兴奋的跨学科领域之一。该计划于2001年宣布完成人类基因组的完整测序。目前,该领域受益于不同科研群体所获得的概念和理论成果,包括遗传学、生物化学和计算机科学。直到最近几年,才发现大量分子生物学问题可被表述为组合优化问题,包括序列比对问题、基因组重排问题、字符串选择与比较问题以及蛋白质结构预测与识别问题。本文详细描述了一些可被表述为组合优化问题的最有趣的分子生物学问题,并针对其中一类特定问题——远离最字符串问题,提出一种新的启发式方法以找到改进的解决方案。

相似文献

1
On some optimization problems in molecular biology.关于分子生物学中的一些优化问题。
Math Biosci. 2007 Jun;207(2):219-34. doi: 10.1016/j.mbs.2006.11.012. Epub 2007 Feb 8.
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A biased random-key genetic algorithm for data clustering.一种用于数据聚类的有偏随机键遗传算法。
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