Mohammadi Jenghara Moslem, Iranpour Mobarakeh Majid, Ebrahimpour Komleh Hossein
PhD, Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran.
PhD, Department of Computer and Electrical Engineering, University of Kashan, Kashan, Iran.
J Biomed Phys Eng. 2021 Dec 1;11(6):675-684. doi: 10.31661/jbpe.v0i0.1119. eCollection 2021 Dec.
Dynamic protein-protein interaction networks (DPPIN) can confirm the conditional and temporal features of proteins and protein complexes. In addition, the relation of protein complexes in dynamic networks can provide useful information in understanding the dynamic functionality of PPI networks.
In this paper, an algorithm is presented to discover the temporal association rule from the dynamic PPIN dataset.
In this analytical study, the static protein-protein interaction network is transformed into a dynamic network using the gene expression thresholding to extract the protein complex relations. The number of presented proteins of the dynamic network is large at each time point. This number will increase for extraction of multidimensional rules at different times. By mapping the gold standard protein complexes as reference protein complexes, the number of items decreases from active proteins to protein complexes at each transaction. Extracted sub graphs as protein complexes, at each time point, are weighted according to the reference protein complexes similarity degrees. Mega-transactions and extended items are created based on occurrence bitmap matrix of the reference complexes. Rules will be extracted based on Mega-transactions of protein complexes.
The proposed method has been evaluated using gold standard protein complex rules. The amount of extracted rules from Biogrid datasets and protein complexes are 281, with support 0.2.
The characteristic of the proposed algorithm is the simultaneous extraction of intra-transaction and inter-transaction rules. The results evaluation using EBI data shows the efficiency of the proposed algorithm.
动态蛋白质-蛋白质相互作用网络（DPPIN）可以确定蛋白质和蛋白质复合物的条件和时间特征。此外，动态网络中蛋白质复合物之间的关系可以为理解蛋白质-蛋白质相互作用网络的动态功能提供有用信息。
本文提出一种从动态PPIN数据集中发现时间关联规则的算法。
在这项分析研究中，利用基因表达阈值将静态蛋白质-蛋白质相互作用网络转化为动态网络，以提取蛋白质复合物关系。动态网络在每个时间点呈现的蛋白质数量众多。在不同时间提取多维规则时，这个数量还会增加。通过将金标准蛋白质复合物映射为参考蛋白质复合物，每次交易中从活性蛋白质到蛋白质复合物的项目数量减少。在每个时间点，作为蛋白质复合物提取的子图根据参考蛋白质复合物的相似度进行加权。基于参考复合物的出现位图矩阵创建超级事务和扩展项目。将根据蛋白质复合物的超级事务提取规则。
已使用金标准蛋白质复合物规则对所提出的方法进行评估。从生物网格数据集和蛋白质复合物中提取的规则数量为281条，支持度为0.2。
所提出算法的特点是同时提取事务内和事务间规则。使用欧洲生物信息研究所（EBI）数据进行的结果评估表明了所提算法的有效性。
