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A Computational Analysis of Protein Sequences for Cyclophilin Superfamily using Feature Extraction

机译:利用特征提取对亲环蛋白超家族蛋白质序列进行计算分析

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Bioinformatics has emerged as one of the most challenging research area which combines machine learning and biological techniques for analysis of biological sequence data. The protein sequence classification is an important task in the field of Bioinformatics. The main aim is to process such data so that it can be made usable to be provided as input to the machine learning algorithm. In this paper, a feature extraction approach is used for converting protein sequences of cyclophilin superfamily into the feature vectors. The feature vectors are then fed as an input to three classifiers, i.e. SVM, K-NN, NB. The experimentation results are presented in the form of performance analysis of all three classifiers in terms of classification of protein sequences of cyclophilin superfamily.
机译:生物信息学已经成为最具挑战性的研究领域之一,它结合了机器学习和生物技术来分析生物序列数据。蛋白质序列分类是生物信息学领域的重要任务。主要目的是处理此类数据,以便可以将其用作机器学习算法的输入。在本文中,使用特征提取方法将亲环蛋白超家族的蛋白质序列转换为特征向量。然后将特征向量作为输入提供给三个分类器,即SVM,K-NN,NB。根据对亲环蛋白超家族蛋白序列的分类,以所有三个分类器的性能分析的形式给出了实验结果。

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