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基于模糊积分的蛋白质序列无对齐相似性分析。

Alignment-free similarity analysis for protein sequences based on fuzzy integral.

机构信息

Institute of Advanced Study in Science and Technology, Mathematical Sciences Division, Guwahati, 781035, India.

Tripura University, Department of Mathematics, Agartala, 799022, India.

出版信息

Sci Rep. 2019 Feb 26;9(1):2775. doi: 10.1038/s41598-019-39477-8.

Abstract

Sequence comparison is an essential part of modern molecular biology research. In this study, we estimated the parameters of Markov chain by considering the frequencies of occurrence of the all possible amino acid pairs from each alignment-free protein sequence. These estimated Markov chain parameters were used to calculate similarity between two protein sequences based on a fuzzy integral algorithm. For validation, our result was compared with both alignment-based (ClustalW) and alignment-free methods on six benchmark datasets. The results indicate that our developed algorithm has a better clustering performance for protein sequence comparison.

摘要

序列比对是现代分子生物学研究的重要组成部分。在这项研究中,我们通过考虑每个无比对蛋白质序列中所有可能氨基酸对的出现频率来估计马尔可夫链的参数。这些估计的马尔可夫链参数用于根据模糊积分算法计算两个蛋白质序列之间的相似性。为了验证,我们的结果与六种基准数据集上的基于比对(ClustalW)和无比对方法进行了比较。结果表明,我们开发的算法在蛋白质序列比较方面具有更好的聚类性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cfc/6391537/ca3b015cc51e/41598_2019_39477_Figa_HTML.jpg

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