Faculty Publications

Document Type

Article

Journal/Book/Conference Title Title

BMC Systems Biology

Volume

6

Issue

Suppl 3

First Page

S2

Abstract

Background: Protein-protein interaction (PPI) networks carry vital information about proteins’ functions. Analysis of PPI networks associated with specific disease systems including cancer helps us in the understanding of the complex biology of diseases. Specifically, identification of similar and frequently occurring patterns (network motifs) across PPI networks will provide useful clues to better understand the biology of the diseases.

Results: In this study, we developed a novel pattern-mining algorithm that detects cancer associated functional subgraphs occurring in multiple cancer PPI networks. We constructed nine cancer PPI networks using differentially expressed genes from the Oncomine dataset. From these networks we discovered frequent patterns that occur in all networks and at different size levels. Patterns are abstracted subgraphs with their nodes replaced by node cluster IDs. By using effective canonical labeling and adopting weighted adjacency matrices, we are able to perform graph isomorphism test in polynomial running time. We use a bottom-up pattern growth approach to search for patterns, which allows us to effectively reduce the search space as pattern sizes grow. Validation of the frequent common patterns using GO semantic similarity showed that the discovered subgraphs scored consistently higher than the randomly generated subgraphs at each size level. We further investigated the cancer relevance of a select set of subgraphs using literature-based evidences.

Conclusion: Frequent common patterns exist in cancer PPI networks, which can be found through effective pattern mining algorithms. We believe that this work would allow us to identify functionally relevant and coherent subgraphs in cancer networks, which can be advanced to experimental validation to further our understanding of the complex biology of cancer.

Department

Department of Chemistry and Biochemistry

Comments

First published in BMC Systems Biology, v.6 n.Suppl 3 (2016), p. S2, by BioMed Central Ltd. DOI: http://dx.doi.org/10.1186/1752-0509-6-S3-S2

Original Publication Date

2012

DOI of published version

10.1186/1752-0509-6-S3-S2

Repository

UNI ScholarWorks, University of Northern Iowa, Rod Library

Date Digital

2012

Copyright

©2012 Ru Shen, Nalin C. W. Goonesekere, and Chittibabu Guda. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

Language

EN

File Format

application/pdf

Included in

Chemistry Commons

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