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Comparative analysis of housekeeping and tissue-specific driver nodes in human protein interaction networks

Overview of attention for article published in BMC Bioinformatics, September 2016
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Title
Comparative analysis of housekeeping and tissue-specific driver nodes in human protein interaction networks
Published in
BMC Bioinformatics, September 2016
DOI 10.1186/s12859-016-1233-0
Pubmed ID
Authors

Xiao-Fei Zhang, Le Ou-Yang, Dao-Qing Dai, Meng-Yun Wu, Yuan Zhu, Hong Yan

Abstract

Several recent studies have used the Minimum Dominating Set (MDS) model to identify driver nodes, which provide the control of the underlying networks, in protein interaction networks. There may exist multiple MDS configurations in a given network, thus it is difficult to determine which one represents the real set of driver nodes. Because these previous studies only focus on static networks and ignore the contextual information on particular tissues, their findings could be insufficient or even be misleading. In this study, we develop a Collective-Influence-corrected Minimum Dominating Set (CI-MDS) model which takes into account the collective influence of proteins. By integrating molecular expression profiles and static protein interactions, 16 tissue-specific networks are established as well. We then apply the CI-MDS model to each tissue-specific network to detect MDS proteins. It generates almost the same MDSs when it is solved using different optimization algorithms. In addition, we classify MDS proteins into Tissue-Specific MDS (TS-MDS) proteins and HouseKeeping MDS (HK-MDS) proteins based on the number of tissues in which they are expressed and identified as MDS proteins. Notably, we find that TS-MDS proteins and HK-MDS proteins have significantly different topological and functional properties. HK-MDS proteins are more central in protein interaction networks, associated with more functions, evolving more slowly and subjected to a greater number of post-translational modifications than TS-MDS proteins. Unlike TS-MDS proteins, HK-MDS proteins significantly correspond to essential genes, ageing genes, virus-targeted proteins, transcription factors and protein kinases. Moreover, we find that besides HK-MDS proteins, many TS-MDS proteins are also linked to disease related genes, suggesting the tissue specificity of human diseases. Furthermore, functional enrichment analysis reveals that HK-MDS proteins carry out universally necessary biological processes and TS-MDS proteins usually involve in tissue-dependent functions. Our study uncovers key features of TS-MDS proteins and HK-MDS proteins, and is a step forward towards a better understanding of the controllability of human interactomes.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 37%
Researcher 7 37%
Student > Bachelor 2 11%
Student > Master 1 5%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 26%
Biochemistry, Genetics and Molecular Biology 3 16%
Medicine and Dentistry 2 11%
Mathematics 2 11%
Psychology 1 5%
Other 3 16%
Unknown 3 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2016.
All research outputs
#6,200,211
of 8,577,291 outputs
Outputs from BMC Bioinformatics
#2,933
of 3,717 outputs
Outputs of similar age
#164,502
of 254,668 outputs
Outputs of similar age from BMC Bioinformatics
#90
of 128 outputs
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