http://iet.metastore.ingenta.com
1887

access icon openaccess Disjoint motif discovery in biological network using pattern join method

Loading full text...

Full text loading...

/deliver/fulltext/iet-syb/13/5/IET-SYB.2019.0008.html;jsessionid=84hdffbpr6jb.x-iet-live-01?itemId=%2fcontent%2fjournals%2f10.1049%2fiet-syb.2019.0008&mimeType=html&fmt=ahah

References

    1. 1)
      • 1. Milo, R., Shen-Orr, S., Itzkovitz, S., et al: ‘Network motifs: simple building blocks of complex networks’, Science, 2002, 298, (5594), pp. 824827.
    2. 2)
      • 2. Mangan, S., Alon, U.: ‘Structure and function of the feed-forward loop network motif’, Proc. Natl. Acad. Sci. USA, 2003, 100, (21), pp. 1198011985.
    3. 3)
      • 3. Alon, U.: ‘Network motifs: theory and experimental approaches’, Nat. Rev. Genetics, 2007, 8, (6), pp. 450461.
    4. 4)
      • 4. Przulj, N., Corneil, D.G., Jurisica, I.: ‘Modeling interactome: scale-free or geometric?’, Bioinformatics, 2004, 20, (18), pp. 35083515.
    5. 5)
      • 5. Milo, R., Itzkovitz, S., Kashtan, N., et al: ‘Superfamilies of evolved and designed networks’, Science, 2004, 303, (5663), pp. 15381542.
    6. 6)
      • 6. Albert, I., Albert, R.: ‘Conserved network motifs allow protein-protein interaction prediction’, Bioinformatics, 2004, 20, (18), pp. 33463352.
    7. 7)
      • 7. Gupta, R., Fayaz, S.M., Singh, S.: ‘Identification of gene network motifs for cancer disease diagnosis’. Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), Mangalore, India, January 2017, pp. 179184.
    8. 8)
      • 8. Chen, L., Qu, X., Cao, M., et al: ‘Identification of breast cancer patients based on human signaling network motifs’, Sci. Rep., 2013, 3368, pp. 17.
    9. 9)
      • 9. Masoudi-Nejad, A., Schreiber, F., Kashani, Z.R.M.: ‘Building blocks of biological networks: a review on major network motif discovery algorithms’, IET Syst. Biol., 2012, 6, (5), pp. 164174.
    10. 10)
      • 10. Wernicke, S.: ‘Efficient detection of network motifs’, IEEE/ACM Trans. Comput. Biol. Bioinf., 2006, 3, (4), pp. 347359.
    11. 11)
      • 11. Kashtan, N., Itzkovitz, S., Milo, R., et al: ‘Network motif detection tool: mfinder tool guide’. Technical report 2005, Departments of Molecular Cell Biology and Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel, 2005.
    12. 12)
      • 12. Schreiber, F., Schwobbermeyer, H.: ‘MAVisto: a tool for the exploration of network motifs’, Bioinformatics, 2005, 21, (17), pp. 35723574.
    13. 13)
      • 13. Chen, J., Hsu, W., Lee, M.L., et al: ‘Nemofinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs’. Proc. of the 12th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, 2006, pp. 106115.
    14. 14)
      • 14. Kashani, Z.R.M., Ahrabian, H., Elahi, E., et al: ‘Kavosh: a new algorithm for finding network motifs’, BMC Bioinf., 2009, 10, (1), p. 318.
    15. 15)
      • 15. Wernicke, S., Rasche, F.: ‘FANMOD: a tool for fast network motif detection’, Bioinformatics, 2006, 22, (9), pp. 11521153.
    16. 16)
      • 16. Grochow, J.A., Kellis, M.: ‘Network motif discovery using subgraph enumeration and symmetry-breaking’. Annual Int. Conf. on Research in Computational Molecular Biology, Berlin, Heidelberg, 2007, pp. 92106.
    17. 17)
      • 17. Omidi, S., Schreiber, F., Masoudi-Nejad, A.: ‘MODA: an efficient algorithm for network motif discovery in biological networks’, Genes Genet. Syst., 2009, 84, (5), pp. 385395.
    18. 18)
      • 18. Kashtan, N., Itzkovitz, S., Milo, R., et al: ‘Efficient sampling algorithm for estimating sub-graph concentrations and detecting network motifs’, Bioinformatics, 2004, 20, pp. 17461758.
    19. 19)
      • 19. McKay, B.D.: ‘Practical graph isomorphism’, Congressus Numerantium, 1981, 30, pp. 4587.
    20. 20)
      • 20. Schreiber, F., Schwobbermeyer, H.: ‘Frequency concepts and pattern detection for the analysis of motifs in networks’. Transactions on Computational Systems Biology III, Berlin, Heidelberg, 2005, pp. 89104.
    21. 21)
      • 21. Liang, C., Li, Y., Luo, J., et al: ‘A novel motif-discovery algorithm to identify co-regulatory motifs in large transcription factor and microRNA co-regulatory networks in human’, Bioinformatics, 2015, 31, (14), pp. 23482355.
    22. 22)
      • 22. Elhesha, R., Kahveci, T.: ‘Identification of large disjoint motifs in biological networks’, BMC Bioinformatics, 2016, 17, (1), p. 408.
    23. 23)
      • 23. Lin, W., Xiao, X., Xie, X., et al: ‘Network motif discovery: a GPU approach’, IEEE Trans. Knowl. Data Eng., 2017, 29, (3), pp. 513528.
    24. 24)
      • 24. Chen, Y., Chen, Y.: ‘An efficient sampling algorithm for network motif detection’, J. Comput. Graph. Stat., 2018, 27, (3), pp. 503515.
    25. 25)
      • 25. Ciriello, G., Guerra, C.: ‘A review on models and algorithms for motif discovery in protein-protein interaction networks’, Briefings in Functional Genomics Proteomics, 2008, 7, (2), pp. 147156.
    26. 26)
      • 26. Ribeiro, P., Silva, F., Kaiser, M.: ‘Strategies for network motifs discovery’. Fifth IEEE Int. Conf. on e-Science, Oxford, UK, 2009, pp. 8087.
    27. 27)
      • 27. Kuramochi, M., Karypis, G.: ‘Finding frequent patterns in a large sparse graph’. SIAM Int. Conf. on Data Mining (SDM-04), Lake Buena Vista, Florida, 2004.
    28. 28)
      • 28. Shen-Orr, S.S., Milo, R., Mangan, S., et al: ‘Network motifs in the transcriptional regulation network of Escherichia coli’, Nat. Genet., 2002, 31, (1), pp. 6468.
    29. 29)
      • 29. Pagel, P., Kovac, S., Oesterheld, M., et al: ‘The MIPS mammalian protein-protein interaction database’, Bioinformatics, 2005, 21, (6), pp. 832834.
    30. 30)
      • 30. Chatr-Aryamontri, A., Ceol, A., Palazzi, L.M., et al: ‘MINT: the molecular INTeraction database’, Nucleic Acids Res., 2007, 35, pp. D572D574.
    31. 31)
      • 31. Li, C., Kim, W.: ‘Discovering larger network motifs: network clustering for network motif discovery’.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-syb.2019.0008
Loading

Related content

content/journals/10.1049/iet-syb.2019.0008
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address