InterDB, a Prediction-Oriented Protein Interaction Database for C. elegans

  • Nicolas Thierry-Mieg
  • Laurent Trilling
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2066)


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.


Association Rule Frequent Itemset Data Mining Technique Inductive Logic Programming Horn Clause 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Nicolas Thierry-Mieg
    • 1
  • Laurent Trilling
    • 1
  1. 1.Laboratoire LSR-IMAGSaint-Martin-d’Hères cedexFrance

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