Table of Contents Author Guidelines Submit a Manuscript
Complexity
Volume 2017, Article ID 4120506, 11 pages
https://doi.org/10.1155/2017/4120506
Research Article

Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC

1School of Computer Science, Shaanxi Normal University, Xi’an, Shaanxi 710119, China
2School of Mathematical Sciences, Nankai University, Tianjin 300071, China
3Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9

Correspondence should be addressed to Xiujuan Lei; nc.ude.unns@ieljx and Fang-Xiang Wu; ac.ksasu.liam@143waf

Received 31 March 2017; Accepted 2 July 2017; Published 28 August 2017

Academic Editor: Juan A. Almendral

Copyright © 2017 Jie Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. E. A. Winzeler, D. D. Shoemaker, A. Astromoff et al., “Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis,” Science, vol. 285, no. 5429, pp. 901–906, 1999. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Lakizadeh, S. Jalili, and S.-A. Marashi, “PCD-GED: Protein complex detection considering PPI dynamics based on time series gene expression data,” Journal of Theoretical Biology, vol. 378, pp. 31–38, 2015. View at Publisher · View at Google Scholar · View at Scopus
  3. A. J. Link, J. Eng, D. M. Schieltz et al., “Direct analysis of protein complexes using mass spectrometry,” Nature Biotechnology, vol. 17, no. 7, pp. 676–682, 1999. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Ho, A. Gruhler, A. Heilbut et al., “Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry,” Nature, vol. 415, no. 6868, pp. 180–183, 2002. View at Publisher · View at Google Scholar · View at Scopus
  5. A. Gavin, M. Bösche, R. Krause et al., “Functional organization of the yeast proteome by systematic analysis of protein complexes,” Nature, vol. 415, no. 6868, pp. 141–147, 2002. View at Publisher · View at Google Scholar · View at Scopus
  6. X. Lei, Y. Ding, H. Fujita, and A. Zhang, “Identification of dynamic protein complexes based on fruit fly optimization algorithm,” Knowledge-Based Systems, vol. 105, pp. 270–277, 2016. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Bertolaso, A. Giuliani, and L. De Gara, “Systems biology reveals biology of systems,” Complexity, vol. 16, no. 6, pp. 10–16, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. G. D. Bader and C. W. V. Hogue, “An automated method for finding molecular complexes in large protein interaction networks,” BMC Bioinformatics, vol. 4, no. 1, p. 2, 2003. View at Publisher · View at Google Scholar · View at Scopus
  9. G. Liu, L. Wong, and H. N. Chua, “Complex discovery from weighted PPI networks,” Bioinformatics, vol. 25, no. 15, pp. 1891–1897, 2009. View at Publisher · View at Google Scholar · View at Scopus
  10. T. Nepusz, H. Yu, and A. Paccanaro, “Detecting overlapping protein complexes in protein-protein interaction networks,” Nature Methods, vol. 9, no. 5, pp. 471-472, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. A.-C. Gavin, P. Aloy, P. Grandi et al., “Proteome survey reveals modularity of the yeast cell machinery,” Nature, vol. 440, no. 7084, pp. 631–636, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. H. C. Leung, Q. Xiang, S. M. Yiu, and F. Y. Chin, “Predicting protein complexes from {PPI} data: a core-attachment approach,” Journal of Computational Biology, vol. 16, no. 2, pp. 133–144, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  13. M. Wu, X. Li, C.-K. Kwoh, and S.-K. Ng, “A core-attachment based method to detect protein complexes in PPI networks,” BMC Bioinformatics, vol. 10, article 169, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. R. V. Solé, R. Ferrer-Cancho, J. M. Montoya, and S. Valverde, “Selection, tinkering, and emergence in complex networks. Crossing the land of tinkering,” Complexity, vol. 8, no. 1, pp. 20–33, 2002. View at Publisher · View at Google Scholar · View at MathSciNet
  15. B. Chen, W. Fan, J. Liu, and F. X. Wu, “Identifying protein complexes and functional modules—from static PPI networks to dynamic PPI networks,” Briefings in Bioinformatics, vol. 15, no. 2, pp. 177–179, 2014. View at Publisher · View at Google Scholar
  16. J. Wang, X. Peng, M. Li, Y. Luo, and Y. Pan, “Active protein interaction network and its application on protein complex detection,” in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM '11), pp. 37–42, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Zhang, H. Lin, Z. Yang, J. Wang, Y. Li, and B. Xu, “Protein complex prediction in large ontology attributed protein-protein interaction networks,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 3, pp. 729–741, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. S. M. Van Dongen, Graph clustering by flow simulation, 2001.
  19. H. Wu, L. Gao, J. Dong, and X. Yang, “Detecting overlapping protein complexes by rough-fuzzy clustering in protein-protein interaction networks,” PLoS ONE, vol. 9, no. 3, Article ID e91856, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. P. Manikandan, D. Ramyachitra, and D. Banupriya, “Detection of overlapping protein complexes in gene expression, phenotype and pathways of Saccharomyces cerevisiae using Prorank based Fuzzy algorithm,” Gene, vol. 580, no. 2, pp. 144–158, 2016. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Zhao, X. Lei, and F. Wu, “Identifying protein complexes in dynamic protein-protein interaction networks based on Cuckoo Search algorithm,” in Proceedings of the 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1288–1295, Shenzhen, China, December 2016. View at Publisher · View at Google Scholar
  22. X. Lei, F. Wang, F.-X. Wu, A. Zhang, and W. Pedrycz, “Protein complex identification through Markov clustering with firefly algorithm on dynamic protein-protein interaction networks,” Information Sciences, vol. 329, pp. 303–316, 2016. View at Publisher · View at Google Scholar · View at Scopus
  23. J. Zeng, D. Li, Y. Wu, Q. Zou, and X. Liu, “An empirical study of features fusion techniques for protein-protein interaction prediction,” Current Bioinformatics, vol. 11, no. 1, pp. 4–12, 2016. View at Publisher · View at Google Scholar
  24. F. Luo, J. Liu, and J. Li, “Discovering conditional co-regulated protein complexes by integrating diverse data sources,” BMC Systems Biology, vol. 4, no. 2, article no. 4, 2010. View at Publisher · View at Google Scholar · View at Scopus
  25. M. Li, X. Wu, J. Wang, and Y. Pan, “Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression data,” BMC Bioinformatics, vol. 13, no. 1, article 109, 2012. View at Publisher · View at Google Scholar · View at Scopus
  26. C. Tu, “A dynamical method to estimate gene regulatory networks using time-series data,” Complexity, vol. 21, no. 2, pp. 134–144, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  27. X. Tang, J. Wang, B. Liu, M. Li, G. Chen, and Y. Pan, “A comparison of the functional modules identified from time course and static PPI network data,” BMC Bioinformatics, vol. 12, article no. 339, 2011. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Wang, X. Peng, M. Li, and Y. Pan, “Construction and application of dynamic protein interaction network based on time course gene expression data,” Proteomics, vol. 13, no. 2, pp. 301–312, 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. C. C. Friedel and R. Zimmer, “Inferring topology from clustering coefficients in protein-protein interaction networks,” BMC Bioinformatics, vol. 7, no. 1, article 519, 2006. View at Publisher · View at Google Scholar · View at Scopus
  30. F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Paris, “Defining and identifying communities in networks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 9, pp. 2658–2663, 2004. View at Publisher · View at Google Scholar · View at Scopus
  31. X. Shang, Y. Wang, and B. Chen, “Identifying essential proteins based on dynamic protein-protein interaction networks and RNA-Seq datasets,” Science China Information Sciences, vol. 59, no. 7, Article ID 070106, 2016. View at Publisher · View at Google Scholar · View at Scopus
  32. X.-S. Yang, Nature-inspired metaheuristic algorithms, Luniver Press, 2010.
  33. A. M. Reynolds and C. J. Rhodes, “The Lévy flight paradigm: Random search patterns and mechanisms,” Ecology, vol. 90, no. 4, pp. 877–887, 2009. View at Publisher · View at Google Scholar · View at Scopus
  34. I. Xenarios, Ł. Salwínski, X. J. Duan, P. Higney, S.-M. Kim, and D. Eisenberg, “DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions,” Nucleic Acids Research, vol. 30, no. 1, pp. 303–305, 2002. View at Publisher · View at Google Scholar · View at Scopus
  35. N. J. Krogan, G. Cagney, H. Yu et al., “Global landscape of protein complexes in the yeast Saccharomyces cerevisiae,” Nature, vol. 440, no. 7084, pp. 637–643, 2006. View at Publisher · View at Google Scholar · View at Scopus
  36. U. Güldener, M. Münsterkötter, M. Oesterheld et al., “MPact: the MIPS protein interaction resource on yeast.,” Nucleic acids research., vol. 34, pp. D436–441, 2006. View at Publisher · View at Google Scholar · View at Scopus
  37. B. P. Tu, A. Kudlicki, M. Rowicka, and S. L. McKnight, “Cell biology: Logic of the yeast metabolic cycle: Temporal compartmentalization of cellular processes,” Science, vol. 310, no. 5751, pp. 1152–1158, 2005. View at Publisher · View at Google Scholar · View at Scopus
  38. S. Pu, J. Wong, B. Turner, E. Cho, and S. J. Wodak, “Up-to-date catalogues of yeast protein complexes,” Nucleic Acids Research, vol. 37, no. 3, pp. 825–831, 2009. View at Publisher · View at Google Scholar · View at Scopus
  39. P. Baldi, S. Brunak, Y. Chauvin, C. A. F. Andersen, and H. Nielsen, “Assessing the accuracy of prediction algorithms for classification: an overview,” Bioinformatics, vol. 16, no. 5, pp. 412–424, 2000. View at Publisher · View at Google Scholar
  40. X. Lei, Y. Ding, and F.-X. Wu, “Detecting protein complexes from DPINs by density based clustering with Pigeon-Inspired Optimization Algorithm,” Science China Information Sciences, vol. 59, no. 7, Article ID 070103, 2016. View at Publisher · View at Google Scholar · View at Scopus
  41. M. Altaf-Ul-Amin, Y. Shinbo, K. Mihara, K. Kurokawa, and S. Kanaya, “Development and implementation of an algorithm for detection of protein complexes in large interaction networks,” BMC Bioinformatics, vol. 7, article 207, 2006. View at Publisher · View at Google Scholar · View at Scopus