Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

Ashwini Patil, Kenta Nakai, Kengo Kinoshita

Research output: Contribution to conferencePaper

8 Citations (Scopus)

Abstract

Background: Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of proteinprotein interaction networks. Results: We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher coexpression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions: We observe that co-expression stability shows distinct patterns in structurally and functionally different groups of proteins and interactions. We conclude that it is a useful and important measure to be used in concert with gene co-expression correlation for further insights into the characteristics of proteins in the context of their interaction network.

Original languageEnglish
DOIs
Publication statusPublished - 2011 Dec 1
Event10th International Conference on Bioinformatics and 1st ISCB Asia Joint Conference 2011: Computational Biology, InCoB 2011/ISCB-Asia 2011 - Kuala Lumpur, Malaysia
Duration: 2011 Nov 302011 Dec 2

Other

Other10th International Conference on Bioinformatics and 1st ISCB Asia Joint Conference 2011: Computational Biology, InCoB 2011/ISCB-Asia 2011
CountryMalaysia
CityKuala Lumpur
Period11/11/3011/12/2

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software
  • Biotechnology
  • Genetics

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    Patil, A., Nakai, K., & Kinoshita, K. (2011). Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks. Paper presented at 10th International Conference on Bioinformatics and 1st ISCB Asia Joint Conference 2011: Computational Biology, InCoB 2011/ISCB-Asia 2011, Kuala Lumpur, Malaysia. https://doi.org/10.1186/1471-2164-12-S3-S19