Diffusion model based spectral clustering for protein-protein interaction networks.
Diffusion model based spectral clustering for protein-protein interaction networks.
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DOI：
10.1371/journal.pone.0012623
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发表时间：
2010-09-07
期刊：
影响因子：
3.7
通讯作者：
Kurata H
中科院分区：
文献类型：
--
作者：
Inoue K;Li W;Kurata H
系统生物学的目标是分析包括基因表达和蛋白质-蛋白质相互作用在内的大规模分子网络，揭示网络结构与其生物学功能之间的关系。将蛋白质-蛋白质相互作用（PPI）网络划分为自然分组的部分是研究网络拓扑结构与其功能之间关系的重要途径。然而，由于PPI网络的异构或无标度特性，明确的模块化分解通常是困难的。为了解决这一问题，我们提出了一种基于扩散模型的谱聚类算法，将PPI网络的聚类结构解析为扩散过程中的随机游走问题。针对网络的异构性，引入功率因子，根据节点度矩阵对过渡（邻接）矩阵进行加权，调整扩散矩阵。该算法被命名为基于可调扩散矩阵的谱聚类算法（ADMSC）。为了证明ADMSC的可行性，我们将其应用于酵母PPI网络的分解，识别出大小大致相等的具有生物学意义的集群。与其他已建立的算法相比，ADMSC有助于清晰快速地分解PPI网络。ADMSC是通过引入功率因数来调节扩散矩阵以适应PPI网络的异质性而提出的。ADMSC有效地将PPI网络划分为几乎相等大小的具有生物学意义的集群，同时非常快速、健壮和简单。
A goal of systems biology is to analyze large-scale molecular networks including gene expressions and protein-protein interactions, revealing the relationships between network structures and their biological functions. Dividing a protein-protein interaction (PPI) network into naturally grouped parts is an essential way to investigate the relationship between topology of networks and their functions. However, clear modular decomposition is often hard due to the heterogeneous or scale-free properties of PPI networks. To address this problem, we propose a diffusion model-based spectral clustering algorithm, which analytically solves the cluster structure of PPI networks as a problem of random walks in the diffusion process in them. To cope with the heterogeneity of the networks, the power factor is introduced to adjust the diffusion matrix by weighting the transition (adjacency) matrix according to a node degree matrix. This algorithm is named adjustable diffusion matrix-based spectral clustering (ADMSC). To demonstrate the feasibility of ADMSC, we apply it to decomposition of a yeast PPI network, identifying biologically significant clusters with approximately equal size. Compared with other established algorithms, ADMSC facilitates clear and fast decomposition of PPI networks. ADMSC is proposed by introducing the power factor that adjusts the diffusion matrix to the heterogeneity of the PPI networks. ADMSC effectively partitions PPI networks into biologically significant clusters with almost equal sizes, while being very fast, robust and appealing simple.
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