Abstract
We consider the problem of using graph-theoretical techniques to predict the function of unannotated proteins in an organism’s proteome. Specifically, we present an overview of the major methods for predicting protein function based on interaction network structure and describe an abstract framework within which these methods can be treated in a unified fashion. We also present a comparison of the proposed methods and highlight some open theoretical and practical questions in the area.
Keywords
MSC2000: Primary 46N60; Secondary 05C85, 05C90
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References
Altschul SF et al (1990) Basic local alignment search tool. J Mol Biol 215:403–410
Altschul SF et al (1997) Gap-blast and psi-blast: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389–3402
Ashburner M et al (2000) Gene ontology: tool for the unification of biology. Nat Genet 25: 25–29
Baldi P, Hatfield GW (2002) DNA microarrays and gene expression. Cambridge University Press, Cambridge
Barabasi L, Oltvai Z (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113
Breitkreutz BJ et al (2003) The GRID: the general repository for interaction datasets. Genome Biol 4:R23
Brun C et al (2003) Functional classification of proteins for the prediction of cellular function from a protein–protein interaction network. Genome Biol 5:R6
Bu D et al (2003) Topological structure analysis of the protein–protein interaction network in budding yeast. Nucleic Acids Res 31(9):2443–2450
Chua H, Sung W, Wong L (2006) Exploiting indirect neighbours and topological weight to predict protein function from protein–protein interactions. Bioinformatics 22(13):1623–1630
Costanzo M et al (2001) YPD, PombePD and WormPD: model organism volumes of the bioknowledge library, an integrated resource for protein information. Nucleic Acids Res 29(1):75–79
Deng M et al (2003) Prediction of protein function using protein–protein interaction data. J Comput Biol 10(6):947–960
Diestel R (2000) Graph theory. Springer, Berlin
Fawcett T (2005) An introduction to ROC analysis. Pattern Recogn Lett 27(8):861–874
Gavin A et al (2002) Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415:141–147
Giot L et al (2003) A protein interaction map of Drosophilamelanogaster. Science 302: 1727–1736
Hishigaki H et al (2001) Assessment of prediction accuracy of protein function from protein–protein interaction data. Yeast 18:523–531
Ito T et al (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc Natl Acad Sci USA 98(8):4569–4574
Jacq B (2001) Protein function from the perspective of molecular interactions and genetic networks. Brief Bioinform 2(1):38–50
Jeong H, Mason S, Barabasi A, Oltvai Z (2001) Lethality and centrality in protein networks. Nature 411:41–42
Karaoz U et al (2004) Whole-genome annotation by using evidence integration in functional-linkage networks. Proc Natl Acad Sci USA 101:2888–2893
Karp P et al (2002) The ecoCyc database. Nucleic Acids Res 30(1):56–58
Kitano H (2002) Systems biology: a brief overview. Science 295:1662–1664
Letovsky S, Kasif S (2003) Predicting protein function from protein/protein interaction data: a probabilistic approach. Bioinformatics 19:i197–i204
Li S et al (2004) A map of the interactome network of the metazoan C. elegans. Science 303:540–543
Mason O, Verwoerd M (2007) Graph theory and networks in biology. IET Syst Biol 1(2): 89–119
Mewes H et al (2002) MIPS: a database for genomes and protein sequences. Nucleic Acids Res 30(1):31–34
Nabieva E et al (2005) Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps. Bioinformatics 21:i302–i310
Pellegrini M et al (1999) Assigning protein function by comparative genome analysis: protein phylogenetic profiles. Proc Natl Acad Sci USA 96(8):4285–4288
Pereira-Leal J, Enright A, Ouzounis C (2004) Detection of functional modules from protein interaction networks. Protein Struct Funct Bioinform 54:49–57
Przulj N, Wigle D, Jurisica I (2004) Functional topology in a network of protein interactions. Bioinformatics 20(3):340–348
Rain J et al (2001) The protein–protein interaction map of Heliobacter pylori. Nature 409: 211–215
Ruepp A et al (2004) The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes. Nucleic Acids Res 32(18):5539–5545
Samanta M, Liang S (2003) Predicting protein functions from redundancies in large-scale protein interaction networks. Proc Natl Acad Sci USA 100(22):12579–12583
Schwikowski B, Uetz P, Fields S (2000) A network of protein–protein interactions in yeast. Nat Biotechnol 18:1257–1261
Sharan R, Ulitsky I, Shamir R (2007) Network-based prediction of protein function. Mol Syst Biol, 3:88
Sontag E (2004) Some new directions in control theory inspired by systems biology. IET Syst Biol 1:9–18
Twyman RM (2004) Principles of proteomics. Garland Science/BIOS Scientific Publishers (Advanced Text Series), Taylor and Francis, London
Vazquez A et al (2003) Global protein function prediction from protein–protein interaction networks. Nat Biotechnol 21(6):697–700
Venter C et al (2001) The sequence of the human genome. Science 291:1304–1351
Von Mering C et al (2002) Comparative assessment of large-scale data sets of protein–protein interactions. Nature 417:399–403
Xenarios I et al (2000) DIP: the database of interacting proteins. Nucleic Acids Res 28(1): 289–291
Yu H et al (2004) Genomic analysis of essentiality within protein networks. Trends Genet 20(6):227–231
Zhou X, Kao M, Wong W (2002) Transitive functional annotation by shortest-path analysis of gene expression data. Proc Natl Acad Sci USA 99(20):1278312788
Acknowledgements
This work was partially supported by Science Foundation Ireland (SFI) grant 03/RP1/I382 and the Irish Higher Education Authority (HEA) PRTLI Network Mathematics grant. Neither Science Foundation Ireland nor the Higher Education Authority is responsible for any use of data appearing in this publication.
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Mason, O., Verwoerd, M., Clifford, P. (2011). Inference of Protein Function from the Structure of Interaction Networks. In: Dehmer, M. (eds) Structural Analysis of Complex Networks. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4789-6_18
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DOI: https://doi.org/10.1007/978-0-8176-4789-6_18
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