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首页> 外文期刊>BMC Veterinary Research >Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae
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Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae

机译:酿酒酵母蛋白质相互作用网络中日期和党中心识别的特征分析

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BackgroundIt has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae 's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes.ResultsWe extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%.ConclusionsWe study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae' s proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs based on their biological features with acceptable accuracy. If such a hypothesis is correct for other species as well, similar methods can be applied to predict the roles of proteins in those species.
机译:背景技术已经理解,生物网络具有模块化组织,这是其观察到的复杂性的来源。对网络和主题的分析表明,两种类型的中心(派对中心和日期中心)是造成这种复杂性的原因。政党枢纽是地方协调员,因为他们与合作伙伴的共同表达程度很高,而日期枢纽则表现出较低的共同表达程度,被认为是全球联系者。但是,在相关文献中,对于这些概念并没有达成共识,不同的研究报告了它们在不同数据集上的结果。我们调查了酿酒酵母蛋白质的生物学特性与其作为非枢纽,中间连接,聚会枢纽和日期枢纽的作用之间是否存在关联。我们提出了将这四个类别分开的分类器。结果我们从各种来源提取了不同的生物学特性,包括氨基酸序列,结构域内容,重复结构域,功能类别,生物学过程,细胞区室,无序区域和位置特异性得分矩阵。检查几个分类器,并基于平均正确分类率和结果的相关系数选择最佳特征集。我们展示了五个特征集的融合,包括域,特定位置评分矩阵-400,单元格一级和带有两个和一个间隙的构图对的融合提供了最佳的区分,平均正确分类率为77%。蛋白质的已知生物学特征集,并显示结构域,特定位置评分矩阵-400,一级细胞隔室,酿酒酵母蛋白质具有两个和一个缺口的组成对之间存在关联,以及它们在蛋白质中的作用蛋白质相互作用网络为非枢纽,中间连接,聚会枢纽和约会枢纽。这项研究还证实了基于非生物学,当事人中心和约会中心的生物学特征以可接受的准确度预测其可能性。如果这种假设对其他物种也是正确的,则可以使用类似的方法来预测蛋白质在那些物种中的作用。

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