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Organized Modularity in the Interactome: Evidence from the Analysis of Dynamic Organization in the Cell Cycle

Wang, Haiying and Zheng, Huiru (2014) Organized Modularity in the Interactome: Evidence from the Analysis of Dynamic Organization in the Cell Cycle. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11 (6). pp. 1264-1270. [Journal article]

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URL: http://dx.doi.org/10.1109/TCBB.2014.2318715

DOI: doi:10.1109/TCBB.2014.2318715


The organization of global protein interaction networks (PINs) has been extensively studied and heatedly debated. We revisited this issue in the context of the analysis of dynamic organization of a PIN in the yeast cell cycle. Statistically significant bimodality was observed when analyzing the distribution of the differences in expression peak between periodically expressed partners. A close look at their behavior revealed that date and party hubs derived from this analysis have some distinct features. There are no significant differences between them in terms of protein essentiality, expression correlation and semantic similarity derived from Gene Ontology (GO) biological process hierarchy. However, date hubs exhibit significantly greater values than party hubs in terms of semantic similarity derived from both GO molecular function and cellular component hierarchies. Relating to three-dimensional structures, we found that both single - and multi-interface proteins could become date hubs coordinating multiple functions performed at different times while party hubs are mainly multi-interface proteins. Furthermore, we constructed and analyzed a PPI network specific to the human cell cycle and highlighted that the dynamic organization in human interactome is far more complex than the dichotomy of hubs observed in the yeast cell cycle.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:29730
Deposited By: Dr Huiru Zheng
Deposited On:04 Jul 2014 09:27
Last Modified:25 Jan 2016 14:46

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