Search of latent periodicity in amino acid sequences by means of genetic algorithm and dynamic programming.

IF 0.8 4区 数学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Statistical Applications in Genetics and Molecular Biology Pub Date : 2016-10-01 DOI:10.1515/sagmb-2015-0079
Valentina Pugacheva, Alexander Korotkov, Eugene Korotkov
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引用次数: 26

Abstract

The aim of this study was to show that amino acid sequences have a latent periodicity with insertions and deletions of amino acids in unknown positions of the analyzed sequence. Genetic algorithm, dynamic programming and random weight matrices were used to develop a new mathematical algorithm for latent periodicity search. A multiple alignment of periods was calculated with help of the direct optimization of the position-weight matrix without using pairwise alignments. The developed algorithm was applied to analyze amino acid sequences of a small number of proteins. This study showed the presence of latent periodicity with insertions and deletions in the amino acid sequences of such proteins, for which the presence of latent periodicity was not previously known. The origin of latent periodicity with insertions and deletions is discussed.

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基于遗传算法和动态规划的氨基酸序列潜在周期性搜索。
本研究的目的是表明氨基酸序列具有潜在的周期性,在所分析的序列中未知位置的氨基酸插入和缺失。利用遗传算法、动态规划和随机权矩阵,提出了一种新的隐周期搜索数学算法。在不使用成对对齐的情况下,通过直接优化位置-权重矩阵来计算周期的多次对齐。该算法用于分析少量蛋白质的氨基酸序列。本研究表明,在这些蛋白质的氨基酸序列中存在插入和缺失的潜在周期性,这是以前不知道的。讨论了带有插入和删除的潜在周期性的起源。
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来源期刊
Statistical Applications in Genetics and Molecular Biology
Statistical Applications in Genetics and Molecular Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
自引率
11.10%
发文量
8
期刊介绍: Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Both original research and review articles will be warmly received.
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