Yeast protein function motif extraction based on sequence alignment

Khaled Sayed, N. Solouma, Y. Kadah
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引用次数: 1

Abstract

Protein function prediction is one of the most important problems in the field of proteomics since it leads to determining cell functions. Since proteome is divided into clusters, each cluster (group of proteins) should have common characteristics. One of these characteristics is to have the same functions. In this study we try to extract motifs for each sub-function category of yeast proteins. The technique is based on applying multiple sequence alignment (MSA) to all yeast protein function categories. The protein sequences are collected from different data sources as DIP, PIR, and SWISS PROT and CLC program is used to apply the sequence alignment. Threshold is determined for every protein function category to indicate the most common frequent amino acids to be a feature for this category. After implementing the algorithm, sequence is verified with some proteins have the correct functions and the gained results are good. The technique is considered as verification method for protein function prediction
基于序列比对的酵母蛋白功能基序提取
蛋白质功能预测是蛋白质组学领域的重要问题之一,因为它可以确定细胞的功能。由于蛋白质组被分成簇,每个簇(蛋白质组)应该具有共同的特征。这些特征之一是具有相同的功能。在这项研究中,我们试图提取酵母蛋白的每个子功能类别的基序。该技术是基于应用多序列比对(MSA)所有酵母蛋白功能类别。蛋白质序列收集自不同的数据源,如DIP、PIR和SWISS PROT,并使用CLC程序进行序列比对。为每个蛋白质功能类别确定阈值,以表明最常见的氨基酸是该类别的特征。算法实现后,对序列进行了验证,其中部分蛋白质功能正确,所得结果良好。该技术可作为蛋白质功能预测的验证方法
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