School of Information Science and Engineering, Central South University, Changsha, 410083, China.
BMC Bioinformatics. 2011 Aug 15;12:339. doi: 10.1186/1471-2105-12-339.
Cellular systems are highly dynamic and responsive to cues from the environment. Cellular function and response patterns to external stimuli are regulated by biological networks. A protein-protein interaction (PPI) network with static connectivity is dynamic in the sense that the nodes implement so-called functional activities that evolve in time. The shift from static to dynamic network analysis is essential for further understanding of molecular systems.
In this paper, Time Course Protein Interaction Networks (TC-PINs) are reconstructed by incorporating time series gene expression into PPI networks. Then, a clustering algorithm is used to create functional modules from three kinds of networks: the TC-PINs, a static PPI network and a pseudorandom network. For the functional modules from the TC-PINs, repetitive modules and modules contained within bigger modules are removed. Finally, matching and GO enrichment analyses are performed to compare the functional modules detected from those networks.
The comparative analyses show that the functional modules from the TC-PINs have much more significant biological meaning than those from static PPI networks. Moreover, it implies that many studies on static PPI networks can be done on the TC-PINs and accordingly, the experimental results are much more satisfactory. The 36 PPI networks corresponding to 36 time points, identified as part of this study, and other materials are available at http://bioinfo.csu.edu.cn/txw/TC-PINs.
细胞系统高度动态，对外界环境的线索做出反应。细胞功能和对外界刺激的反应模式受到生物网络的调节。具有静态连通性的蛋白质-蛋白质相互作用（PPI）网络在某种意义上是动态的，即节点实现所谓的随时间演变的功能活动。从静态网络分析向动态网络分析的转变对于进一步理解分子系统至关重要。
在本文中，通过将时间序列基因表达纳入 PPI 网络，重建了时程蛋白相互作用网络（TC-PINs）。然后，使用聚类算法从三种网络（TC-PINs、静态 PPI 网络和伪随机网络）中创建功能模块。对于 TC-PINs 的功能模块，会删除重复模块和更大模块内的模块。最后，进行匹配和 GO 富集分析，以比较从这些网络中检测到的功能模块。
对比分析表明，TC-PINs 中的功能模块比静态 PPI 网络中的功能模块具有更显著的生物学意义。此外，这意味着许多基于静态 PPI 网络的研究都可以在 TC-PINs 上进行，因此实验结果更加令人满意。作为本研究的一部分，确定了 36 个对应于 36 个时间点的 PPI 网络，以及其他材料可在 http://bioinfo.csu.edu.cn/txw/TC-PINs 上获取。
