一种新的快速蛋白质分类和进化分析方法

IF 2.9 2区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Match-Communications in Mathematical and in Computer Chemistry Pub Date : 2023-04-01 DOI:10.46793/match.90-2.381a
Liang Ai, Jie Feng, Yu-Hua Yao
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引用次数: 0

摘要

本文提出了一种新的蛋白质序列相似性和进化分析的快速无比对方法。首先根据20种天然氨基酸的理化性质将其聚为6类,然后根据氨基酸在每个还原氨基酸序列中出现的频率和平均位置构建一个12维向量。最后,利用欧几里得距离来度量蛋白质序列之间的相似性和进化距离。在三个数据集上的测试表明,我们的方法可以准确地聚类每个蛋白质序列,说明了我们的方法的有效性。
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A Novel Fast Approach for Protein Classification and Evolutionary Analysis
In this paper, we propose a new fast alignment-free method for protein sequence similarity and evolutionary analysis. First 20 natural amino acids are clustered into 6 groups based on their physicochemical properties, then a 12-dimensional vector is constructed based on the frequency and the average position of occurrence of amino acids in each reduced amino acid sequences. Finally, the Euclidean distance is used to measure the similarity and evolutionary distance between protein sequences. The test on three datasets shows that our method can cluster each protein sequence accurately, which illustrates the effective of our method.
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来源期刊
CiteScore
4.40
自引率
26.90%
发文量
71
审稿时长
2 months
期刊介绍: MATCH Communications in Mathematical and in Computer Chemistry publishes papers of original research as well as reviews on chemically important mathematical results and non-routine applications of mathematical techniques to chemical problems. A paper acceptable for publication must contain non-trivial mathematics or communicate non-routine computer-based procedures AND have a clear connection to chemistry. Papers are published without any processing or publication charge.
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