Abstract
Protein-protein interactions are critical to many biological processes, extending from the formation of cellular macromolecular structures and enzymatic complexes to the regulation of signal transduction pathways. With the availability of complete genome sequences, several groups have begun large-scale identification and characterization of such interactions, relying mostly on high-throughput two-hybrid systems. We collaborate with one such group, led by Marc Vidal, whose aim is the construction of a protein-protein interaction map for C. elegans. In this paper we first describe WISTdb, a database designed to store the interaction data generated in Marc Vidal’s laboratory. We then describe InterDB, a multi-organism prediction-oriented database of protein-protein interactions. We finally discuss our current approaches, based on inductive logic programming and on a data mining technique, for extracting predictive rules from the collected data.
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References
The Acembly sequence assembly package, http://alpha.crbm.cnrs-mop.fr/acembly/
Agrawal R., Srikant R. (1994): Fast algorithms for mining association rules. Proceedings of the 20 th VLDB Conference, 487–499
Bairoch A., Apweiler R. (1999): The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1999. Nucleic Acids Research 27(1), 49–54
A. Bateman, E. Birney, R. Durbin, S. Eddy, R.D. Finn, E.L. Sonnhammer(1999): Pfam 3.1: 1313 multiple alignments and profie HMMs match the majority of proteins. Nucleic Acids Research, 27(1), 260–262
The C. elegans Sequencing Consortium (1998), Science 282, 2012–2018
M. Eisen, P. Spellman, P. Brown, D. Botstein (1998): Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863–14868
A. Enright, I. Iliopoulos, N. Kyrpides, C. Ouzounis (1999): Protein interaction maps for complete genomes based on gene fusion events. Nature 402, 86–90
K. Hofmann, P. Bucher, L. Falquet, A. Bairoch(1999): The PROSITE database, its status in 1999. Nucleic Acids Research, 27(1), 215–219
The Kim laboratory, http://cmgm.stanford.edu/~kimlab
The C. elegans Gene Knockout Consortium, http://www.cigenomics.bc.ca/elegans/
Lecrenier N., Foury F., Goffeau A. (1998): Two-hybrid systematic screening of the yeast proteome. BioEssays, 20, 1–5
E. Marcotte, M. Pellegrini, H. Ng, D. Rice, T. Yeates, D. Eisenberg (1999): Detecting protein function and protein-protein interactions from genome sequences. Science, 285, 751–753
Marcotte E., Pellegrini M., Thompson M., Yeates T., Eisenberg D. (1999): A combined algorithm for genome-wide prediction of protein function. Nature 402, 83–86
Manilla H., Toivonen H., Verkamo A. (1994): Efficient algorithms for discovering association rules. KDD-94: AAAI Workshop on Knowledge Discovery in Databases
S. Muggleton, L. De Raedt(1994): Inductive logic programming: theory and methods. Journal of logic programming, 19,20:629–679
S. Muggleton(1995): Inverse entailement and Progol. New generation computing, 13, 245–286
A. Sali (1999): Functional links between proteins. Nature 402, 23–26
Pellegrini M., Marcotte E., Thompson M., Eisenberg D., Yeates T. (1999): Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. Proc. Natl. Acad. Sci. USA 96, 4285–4288
C. Sanchez, C. Lachaize, F. Janody, B. Bellon, L. Röder, J. Euzenat, F. Rechenmann, B. Jacq(1999): Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an internet database. Nucleic Acids Research 27(1), 89–94
L. Stein, J. Thierry-Mieg (1999): Scriptable Access to the Caenorhabditis elegans Genome Sequence and other Acedb Databases. Genome Research 8(12):1308–1315
J. Thierry-Mieg, D. Thierry-Mieg, L. Stein (1999): ACEDB: The ACE database manager. In S. Letovsky (ed.): Bioinformatics, Databases and Systems, Kluwer Academic Publishers, 265–278
Uetz et al. (2000): A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature, 403, 623–627
M. Vidal, P. Legrain (1999): Yeast forward and reverse ‘n’-hybrid systems. Nucleic Acids Research 27(4), 919–929
A. Walhout, H. Endoh, N. Thierry-Mieg, W. Wong, M. Vidal (1999): A model of elegance. American Journal of Human Genetics 63(4):955–61
A. Walhout, R. Sordella, X. Lu, J. Hartley, G. Temple, M. Brasch, N. Thierry-Mieg, M. Vidal (2000): Protein interaction mapping in C. elegans using proteins involved in vulval development. Science, 287, 116–122
Winona C. Barker, John S. Garavelli, Peter B. McGarvey, Christopher R. Marzec, Bruce C. Orcutt, Geetha Y. Srinivasarao, Lai-Su L. Yeh, Robert S. Ledley, Hans-Werner Mewes, Friedhelm Pfeiffer, Akira Tsugita and Cathy Wu (1999): The PIR-International Protein Sequence Database. Nucleic Acids Research 27(1): 39–43
The Yeast Protein Database, http://www.proteome.com/
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Thierry-Mieg, N., Trilling, L. (2001). InterDB, a Prediction-Oriented Protein Interaction Database for C. elegans . In: Gascuel, O., Sagot, MF. (eds) Computational Biology. JOBIM 2000. Lecture Notes in Computer Science, vol 2066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45727-5_12
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DOI: https://doi.org/10.1007/3-540-45727-5_12
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