Exploratory analysis of protein translation regulatory networks using hierarchical random graphs

BMC Bioinformatics

Proceedings

EK Park¹  Jiali Feng²  Xiaofeng Wang²  Daniel D Wu³  Xiaohua Hu³  Xindong Wu⁴ 

[1] CSI-CUNY, 10314, Staten Island, NY, USA;College of Information Engineering, Shanghai Maritime University, Shanghai, China;College of Information Science and Technology, Drexel University, Philadelphia, Pennsylvania, USA;Department of Computer Science, University of Vermont, Vermont, USA;School of Computer Science and Information Engineering, Hefei University of Technology, 230009, Hefei, China;

关键词: Internal Ribosome Entry Site;    Translation Machinery;    eRF3;    Missing Link;    Lower Common Ancestor;   

DOI  :  10.1186/1471-2105-11-S3-S2

来源: Springer

【 摘 要 】

BackgroundProtein translation is a vital cellular process for any living organism. The availability of interaction databases provides an opportunity for researchers to exploit the immense amount of data in silico such as studying biological networks. There has been an extensive effort using computational methods in deciphering the transcriptional regulatory networks. However, research on translation regulatory networks has caught little attention in the bioinformatics and computational biology community.ResultsIn this paper, we present an exploratory analysis of yeast protein translation regulatory networks using hierarchical random graphs. We derive a protein translation regulatory network from a protein-protein interaction dataset. Using a hierarchical random graph model, we show that the network exhibits well organized hierarchical structure. In addition, we apply this technique to predict missing links in the network.ConclusionsThe hierarchical random graph mode can be a potentially useful technique for inferring hierarchical structure from network data and predicting missing links in partly known networks. The results from the reconstructed protein translation regulatory networks have potential implications for better understanding mechanisms of translational control from a system’s perspective.

【 授权许可】

CC BY   
© Hu et al; licensee BioMed Central Ltd. 2010