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Biclustering Protein Interactions Between HIV-1 Proteins and Humans Proteins Using LCM-MBC Algorithm

机译:使用LCM-MBC算法,HIV-1蛋白和人蛋白与人蛋白之间的双峰蛋白质相互作用

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Some of the protein interactions are still unidentified. Thus, many research about protein interactions had been held. HIV-1 is a dangerous virus that has no medicine yet. The research about HIV-1 proteins and human proteins interactions leads to the insight of drug target prediction. Biclustering technique is the beginning step before the prediction step. Biclustering is the process to cluster the dataset through two perspectives. The result of biclustering can be applied to predict unidentified protein interactions. Currently, this technique is more efficiently and effectively than the experimental method. The LCM-MBC is one of the biclustering algorithms to find biclusters from protein interactions dataset. This algorithm uses graph theory as the basic to obtain the maximal biclique. The algorithm can represent as enumeration tree. Every subtree result from the bicliques which are the biclusters. This algorithm performs quickly and efficiently in the term of memory consumptions. In this research, we apply the LCM-MBC algorithm for 16215 types of interactions between HIV-1 proteins and human proteins. We find 852 biclusters which the maximal bicluster has a size of 4 rows and 204 columns.
机译:一些蛋白质相互作用仍然不明。因此,已经举行了许多关于蛋白质相互作用的研究。 HIV-1是一种危险病毒,尚未药物。关于HIV-1蛋白和人蛋白相互作用的研究导致药物靶预测的洞察力。双板技术是预测步骤之前的开始步骤。 BICLUSTING是通过两个透视图聚类数据集的过程。双板胶质的结果可以应用于预测未识别的蛋白质相互作用。目前,该技术比实验方法更有效且有效。 LCM-MBC是从蛋白质相互作用数据集找到双板的双板血管算法之一。该算法使用图形理论作为基本获取最大的Biclique。该算法可以表示为枚举树。每个子树都来自作为双板的双板。该算法在内存消耗的术语中快速有效地执行。在该研究中,我们在HIV-1蛋白和人蛋白之间进行16215种相互作用的LCM-MBC算法。我们发现最大Bicluster的852个Biclusters的大小为4行和204列。

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