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Yeast protein function motif extraction based on sequence alignment

机译:基于序列比对的酵母蛋白功能基序提取

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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
机译:蛋白质功能预测是蛋白质组学领域最重要的问题之一,因为它可导致确定细胞功能。由于蛋白质组被分成簇,每个簇(蛋白质组)应具有共同的特征。这些特征之一是具有相同的功能。在这项研究中,我们尝试为酵母蛋白的每个亚功能类别提取基序。该技术基于对所有酵母蛋白功能类别应用多重序列比对(MSA)。从DIP,PIR和SWISS PROT等不同数据源收集蛋白质序列,并使用CLC程序进行序列比对。确定每个蛋白质功能类别的阈值,以指示最常见的频繁氨基酸成为该类别的特征。实施该算法后,用某些具有正确功能的蛋白质对序列进行验证,所得结果良好。该技术被认为是蛋白质功能预测的验证方法

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