Wang Xiaoting, Zhang Nan, Zhao Yulan, Wang Juan
School of Computer Science, Inner Mongolia University, and with Ecological Big Data Engineering Research Center of the Ministry of Education, Hohhot, China.
Front Genet. 2021 Dec 13;12:792265. doi: 10.3389/fgene.2021.792265. eCollection 2021.
A protein complex is the combination of proteins which interact with each other. Protein-protein interaction (PPI) networks are composed of multiple protein complexes. It is very difficult to recognize protein complexes from PPI data due to the noise of PPI. We proposed a new method, called Topology and Semantic Similarity Network (TSSN), based on topological structure characteristics and biological characteristics to construct the PPI. Experiments show that the TSSN can filter the noise of PPI data. We proposed a new algorithm, called Neighbor Nodes of Proteins (NNP), for recognizing protein complexes by considering their topology information. Experiments show that the algorithm can identify more protein complexes and more accurately. The recognition of protein complexes is vital in research on evolution analysis. Availability and implementation: https://github.com/bioinformatical-code/NNP.
蛋白质复合体是相互作用的蛋白质的组合。蛋白质-蛋白质相互作用（PPI）网络由多个蛋白质复合体组成。由于PPI存在噪声，从PPI数据中识别蛋白质复合体非常困难。我们基于拓扑结构特征和生物学特征提出了一种名为拓扑与语义相似性网络（TSSN）的新方法来构建PPI。实验表明，TSSN可以过滤PPI数据中的噪声。我们提出了一种名为蛋白质邻域节点（NNP）的新算法，通过考虑蛋白质复合体的拓扑信息来识别它们。实验表明，该算法能够更准确地识别更多的蛋白质复合体。蛋白质复合体的识别在进化分析研究中至关重要。可用性与实现方式：https://github.com/bioinformatical-code/NNP 。
