Skip to main content
Springer Nature Link
Log in

Predicting Functional Protein-Protein Interactions Based on Computational Methods

  • Conference paper
Life System Modeling and Simulation (LSMS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4689))

Included in the following conference series:

  • 1635 Accesses

Abstract

Protein-protein interactions play a crucial role in the cellular process. In recent years, yet new experimental techniques have been developed to discover the protein-protein interaction networks, the accuracy and coverage has still proven to be limited. Computational approaches come into being essential both to assist in the design and validation of experimental studies and for the prediction of interacted proteins. This paper presents a survey of the major computational methods for detecting protein-protein interactions, and expatiates on their key contribution by introducing the experimental methods, the typical computational methods and the improvement over them in turn.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Huynen, M., Snel, B., Lathe III, W., Bork, P.: Predicting Protein Function by Genomic Context: Quantitative Evaluation and Qualitative Inferences. Genome Res. 10, 1204–1210 (2000)

    Article  Google Scholar 

  2. Tucker, C.L., Gera, J.F., Uetz, P.: Towards an Understanding of Complex Protein Networks. Trends Cell Biol. 11, 102–106 (2001)

    Article  Google Scholar 

  3. Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S.G., Fields, S., Bork, P.: Comparative Assessment of Large-scale Data Sets of Protein-Protein Interactions. Nature 417, 399–403 (2002)

    Article  Google Scholar 

  4. Bader, G.D., Hogue, C.W.V.: Analyzing Yeast Protein-Protein Interactions Data Obtained From Different Sources. Nature Biotechnology 20, 991–997 (2002)

    Article  Google Scholar 

  5. Deng, M., Mehta, S., Sun, F., Chen, T.: Inferring Domain–Domain Interactions From Protein–Protein Interactions. Genome Res. 12, 1540–1548 (2002)

    Article  Google Scholar 

  6. Enright, A.J., Iliopoulos, I., Kyrpides, N.C., Ouzounis, C.A.: Protein Interactions Maps for Complete Genomes Based on Gene Fusion Events. Nature 402, 86–90 (1999)

    Article  Google Scholar 

  7. Marcotte, E.M., Pellegrini, M., Ng, H.L., Rice, D.W., Yeates, D.O., Eisenberg, D.: Detecting Protein Function and Protein-Protein Interactions From Genome Sequences. Science 285, 751–753 (1999)

    Article  Google Scholar 

  8. Ng, S., Zhang, Z., Tan, S., Lin, K.: InterDom: A Database of Putative Interacting Protein Domains for Validating Predicated Protein Interactions and Complexes. Nucleic Acids Res. 31, 251–254 (2003)

    Article  Google Scholar 

  9. Enright, A.J., Ouzounis, C.A.: Protein-Protein Interactions: A Molecular Cloning Manual. Cold Spring Harbor Laboratory Press, Cold Spring Harbor New York (2002)

    Google Scholar 

  10. Bock, J.R., Gough, D.A.: Prediction of Protein- Protein Interactions from Primary Structure. Bioinformatics 17, 455–460 (2001)

    Article  Google Scholar 

  11. Wojcik, J., Schachter, V.: Protein-Protein Interactions Map Inference Using Interacting Domain Profile Pairs. Bioinformatics 17, S296–S305 (2001)

    Google Scholar 

  12. Han, D., Kim, H., Seo, J., Jang, W.: Domain Combination Based Probabilistic Framework for Protein- Protein Interactions Prediction. Genome Informatics 14, 250–259 (2003)

    Google Scholar 

  13. Fields, S., Song, O.: A novel genetic system to detect protein-protein interactions. Nature 340, 245–246 (1989)

    Article  Google Scholar 

  14. Yates III, J.R.: Mass Spectrometry: From Genomics to Proteomics. Trends Genet. 16, 5–8 (2000)

    Article  Google Scholar 

  15. Yu, J., Fotouhi, F.: Computational Approaches for Predicting Protein–Protein Interactions: A Survey. J. Med. Sys. 30, 39–44 (2006)

    Article  Google Scholar 

  16. Sprinzak, E., Margalit, H.: Correlated Sequence-Signature as Markers of Protein-Protein Interactions. J. Molecular Biology 311, 681–692 (2001)

    Article  Google Scholar 

  17. Hayashida, M., Ueda, N., Akutsu, T.: A Simple Method for Inferring Strengths of Protein-Protein Interactions. Genome Informatics 15, 56–68 (2004)

    Google Scholar 

  18. Matthews, L.R., Vaglio, P., Reboul, J., Ge, H., Davis, B.P., Garrels, J., Vincent, S., Vidal, M.: Identification of Potential Interactions Networks Using Sequence-based Searches for Conserved Protein–Protein Interactions or ”Interologs”. Genome Res. 11, 2120–2126 (2001)

    Article  Google Scholar 

  19. Dandekar, T., Snel, B., Huynen, M., Bork, P.: Conservation of gene order: A fingerprint of Proteins that Physically Interact. Science 23, 324–328 (1998)

    Google Scholar 

  20. Enright, A.J., Iliopoulos, I., Kyrpides, N.C., Ouzounis, C.A.: Protein Interactions Maps for Complete Genomes Based on Gene Fusion Events. Nature 402, 86–90 (1999)

    Article  Google Scholar 

  21. Pellegrini, M., et al.: Assigning Protein Functions by Comparative Genome Analysis: Protein Phylogenetic Profiles. Proc. Natl. Acad. Sci. 96, 4285–4288 (1999)

    Article  Google Scholar 

  22. Szilágyi, A., Grimm, V., Arakaki, A.K., Skolnick, J.: Prediction of Physical Protein-Protein Interactions. Phys. Biol. 2, S1–S16 (2005)

    Article  Google Scholar 

  23. Moore, R., Rajasekar, A., Wan, M.: Data Grids, Digital Libraries, and Persistent Archives: An Integrated Approach to Sharing, Publishing, and Archiving Data. Proceedings of the IEEE 93(3), 578–588 (2005)

    Article  Google Scholar 

  24. BioGRID, http://www.thebiogrid.org

  25. Hu, X., Song, I.Y., et al.: Extracting and mining protein-protein interactions network from biomedical literature. Computational Intelligence in Bioinformatics and Computational Biology, 244–251 (2004)

    Google Scholar 

  26. Nafar, Z., Golshani, A.: Data Mining Methods for Protein-Protein Interactions, Electrical and Computer Engineering. In: Canadian Conference on, pp. 991–994 (May 2006)

    Google Scholar 

  27. Huang, C., Morcos, F., Kanaan, S.P., Wuchty, S., Chen, D.Z., Izaguirre, J.A.: Predicting Protein-Protein Interactions from Protein Domains Using a Set Cover Approach, Computational Biology and Bioinformatics. IEEE/ACM Transactions 4(1), 78–87 (2007)

    Google Scholar 

  28. Pearl, F.M.G., et al.: Assigning Genomic Sequences to CATH. Nucleic Acids Res. 28, 277–282 (2000)

    Article  MathSciNet  Google Scholar 

  29. Chen, X., Liu, M.: Prediction of Protein-Protein Interactions Using Random Decision Forest Framework. Bioinformatics 21, 4394–4400 (2005)

    Article  Google Scholar 

  30. Han, D., Kim, H., Jang, W., Lee, S.: Domain Combination Based Protein-Protein Interactions Possibility Ranking Method. In: BIBE 2004. Proceedings of the Fourth IEEE Symposium on Bioinformatics and Bioengineering, IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

  31. Dohkan, S., Koike, A., Takagi, T.: Prediction of Protein-Protein Interactions Using Support Vector Machines. In: BIBE 2004. Proceedings of the Fourth IEEE Symposium on Bioinformatics and Bioengineering, IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

  32. Kemmeren, P., van Berkum, N.L., Vilo, J., Bijma, T., et al.: Protein Interactions Verification and Functional Annotation by Integrated Analysis of Genome-Scale Data. Mol. Cell. 9, 1133–1143 (2002)

    Article  Google Scholar 

  33. Gygi, S., Rochon, Y., Franza, B.R., Aebersold, R.: Correlation between Protein and MRNA Abundance in Yeast. MCB 19, 1720–1730 (1999)

    Google Scholar 

  34. Lee, M., Park, S., Kim, M.: A Protein Interactions Verification System Based on a Neural Network Algorithm. In: CSBW 2005. Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference Workshops, IEEE Computer Society Press, Los Alamitos (2005)

    Google Scholar 

  35. Mamitsuka, H.: Essential Latent Knowledge for Protein-Protein Interactions: Analysis By an Unsupervised Learning Approach, Computational Biology and Bioinformatics. IEEE/ACM Transactions on 2(2), 119–130 (2005)

    Google Scholar 

  36. Uetz, P., Giot, L., Cagney, G., Mansfield, T.A., Judson, R.S., Knight, J.R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., et al.: A Comprehensive Analysis of Protein–Protein Interactions in Saccharomyces Cerevisiae. Nature 403, 623–627 (2000)

    Article  Google Scholar 

  37. Ito, T., Tashiro, K., Muta, S., Ozawa, R., Chiba, T., Nishizawa, M., Yamamoto, K., Kuhara, S., Sakaki, Y.: Toward a Protein-Protein Interactions Map of the Budding Yeast: A Comprehensive System to Examine Two-Hybrid Interactions in All Possible Combinations Between the Yeast Proteins. Proc. Natl. Acad. Sci. 97, 1143–1147 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Shanghai University, Shanghai, 200072, China

    Luwen Zhang & Wu Zhang

Authors
  1. Luwen Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Kang Li Xin Li George William Irwin Gusen He

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, L., Zhang, W. (2007). Predicting Functional Protein-Protein Interactions Based on Computational Methods. In: Li, K., Li, X., Irwin, G.W., He, G. (eds) Life System Modeling and Simulation. LSMS 2007. Lecture Notes in Computer Science(), vol 4689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74771-0_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74771-0_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74770-3

  • Online ISBN: 978-3-540-74771-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics