HSPPIP: An Online Tool for Prediction of Protein–Protein Interactions in Humans

  • Yu Xue
  • Changjiang Jin
  • Xuebiao Yao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4115)


Recently, protein-protein interaction prediction (PPIP) has been emerging as an appealing question. Although several in silico approaches have been developed to delineate the potential protein-protein interaction (PPI), there are few online tools of human PPIP for further experimental design. Here we present an online service, hsPPIP (Protein-Protein Interaction Predicting of Homo Sapiens), to predict or evaluate the potential PPIs in human. The annotations of functional domain (Interpro) and GO (Gene Ontology) for proteins are employed as two informative features, and are integrated by the naïve Bayesian approach. The prediction accuracy is comparable to the existing tools. Based on the hypothesis that the features correlated with PPIs are conserved in different organisms, the web server hsPPIP is established and could predict the PPIs of human dynamically. hsPPIP is implemented in PHP+MySQL and can be freely accessed at: http://973-proteinweb.ustc.edu.cn/ hsppip/.


Gene Ontology Protein Pair Spindle Checkpoint Homo Sapiens Biomolecular Interaction Network Database 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mulder, N.J., Apweiler, R., Attwood, T.K., Bairoch, A.: InterPro, Progress and Status in 2005. Nucleic Acids Res. 33, 201–205 (2005)CrossRefGoogle Scholar
  2. 2.
    Harris, M.A.: The Gene Ontology (GO) Database and Informatics Resource. Nucleic Acids Res. 32, 258–261 (2004)CrossRefGoogle Scholar
  3. 3.
    Hahn, M.W., Kern, A.D.: Comparative Genomics of Centrality and Essentiality in Three Eukaryotic Protein-Interaction Networks. Mol. Biol. E. 22, 803–806 (2004)CrossRefGoogle Scholar
  4. 4.
    Yu, H., Luscombe, N.M., Lu, H.X., Zhu, X., Xia, Y., Han, J.D., Bertin, N., Chung, S., Vidal, M., Gerstein, M.: Annotation Transfer Between Genomes: Protein-protein Interologs and Protein-DNA regulogs. Genome. Res. 14, 1107–1118 (2004)CrossRefGoogle Scholar
  5. 5.
    Jansen, R., Yu, H., Greenbaum, D., Kluger, Y., Krogan, N.J., Chung, S., Emili, A., Snyder, M., Greenblatt, J.F., Gerstein, M.: A Bayesian Networks Aapproach for Predicting Protein-Protein Interactions from Genomic Data. Science 302, 449–453 (2003)CrossRefGoogle Scholar
  6. 6.
    Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., Ideker, T.: Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome. Res. 13, 2498–2504 (2003)CrossRefGoogle Scholar
  7. 7.
    Mrowka, R.: A Java Applet for Visualizing Protein-protein Interaction. Bioinformatics 17, 669–671 (2001)CrossRefGoogle Scholar
  8. 8.
    Shah, J.V., Botvinick, E., Bonday, Z., Furnari, F., Berns, M., Cleveland, D.W.: Dynamics of Centromere and Kinetochore Proteins, Implications for Checkpoint Signaling and Silencing. Curr. Biol. 14, 942–952 (2004)Google Scholar
  9. 9.
    Cahill, D.P., Lengauer, C., Yu, J., Riggins, G.J., Willson, J.K., Markowitz, S.D., Kinzler, K.W., Vogelstein, B.: Mutations of Mitotic Checkpoint Genes in Human Cancers. Nature 392, 300–303 (1998)CrossRefGoogle Scholar
  10. 10.
    Von, M.C., Jensen, L.J., Snel, B., Hooper, S.D., Krupp, M., Foglierini, M., Jouffre, N., Huynen, M.A., Bork, P.: String: Known and Predicted Protein-protein Associations, Integrated and Transferred Across Organisms. Nucleic Acids Res. 33, 433–437 (2005)Google Scholar
  11. 11.
    Mewes, H.W., Amid, C., Arnold, R.: MIPS: Analysis and Annotation of Proteins from Whole Genomes. Nucleic Acids Res. 32, 41–44 (2004)CrossRefGoogle Scholar
  12. 12.
    Alfarano, C., Andrade, C.E., Anthony, K., Bahroos, N., Bajec, M.: The Biomolecular Interaction Network Database and Related Tools 2005 Update. Nucleic Acids Res. 33, 418–424 (2005)CrossRefGoogle Scholar
  13. 13.
    Breitkreutz, B.J., Stark, C., Tyers, M.: The GRID: The General Repository for Interaction Datasets. Genome. Biol. 4(3), 233–245 (2003)Google Scholar
  14. 14.
    Cherry, J.M., Adler, C., Ball, C., Chervitz, S.A.: SGD: Saccharomyces Genome Database. Nucleic Acids Res. 26, 73–79 (1998)CrossRefGoogle Scholar
  15. 15.
    Zanzoni, A., Montecchi-Palazzi, L., Quondam, M., Ausiello, G., Helmer-Citterich, M., Cesareni, G.: MINT: a Molecular INTeraction database. FEBS Lett. 513, 135–140 (2002)CrossRefGoogle Scholar
  16. 16.
    Salwinski, L., Miller, C.S., Smith, A.J., Pettit, F.K., Bowie, J.U., Eisenberg, D.: The Database of Interacting Proteins: 2004 Update. Nucleic Acids Res. 32, 449–451 (2004)CrossRefGoogle Scholar
  17. 17.
    Sprinzak, E., Margalit, H.: Correlated Sequence-signatures as Markers of Protein-protein Interaction. J. Mol Biol. 311, 681–692 (2001)CrossRefGoogle Scholar
  18. 18.
    Kim, W.K., Park, J., Suh, J.K.: Large Scale Statistical Prediction of Protein-protein Interaction by Potentially Interacting Domain (PID) Pair. In: Genome Inform Ser Workshop Genome Inform, vol. 13, pp. 42–50 (2002)Google Scholar
  19. 19.
    Obenauer, J.C., Yaffe, M.B.: Computational Prediction of Protein-protein Interactions. Methods Mol. Biol. 261, 445–468 (2004)Google Scholar
  20. 20.
    Han, D.S., Kim, H.S., Jang, W.H., Lee, S.D., Suh, J.K.: PreSPI: A Domain Combination Based Prediction System for Protein-protein Interaction. Nucleic Acids Res. 32, 6312–6320 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yu Xue
    • 1
  • Changjiang Jin
    • 1
  • Xuebiao Yao
    • 1
    • 2
  1. 1.School of Life ScienceUniversity of Science and Technology of ChinaHefeiP.R. China
  2. 2.Department of PhysiologyMorehouse School of MedicineAtlantaUSA

Personalised recommendations