Abstract
Protein-protein interactions are key to understanding biological processes and disease mechanisms in organisms. There is a vast amount of data on proteins waiting to be explored. In this paper, we describe application of data mining techniques, namely association rule mining and ID3 classification, to the problem of predicting protein-protein interactions. We have combined available interaction data and protein domain decomposition data to infer new interactions. Preliminary results show that our approach helps us find plausible rules to understand biological processes.
This work was partially supported by the Turkish Academy of Sciences to RCA (in the framework of young Scientist Award Program-RCA/TUBA-GEBIP/2001-2-3)
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Christian Borgelt’s Software Page, http://fuzzy.cs.uni-magdeburg.de/~borgelt/
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Kocatas, A., Gursoy, A., Atalay, R. (2003). Application of Data Mining Techniques to Protein-Protein Interaction Prediction . In: Yazıcı, A., Şener, C. (eds) Computer and Information Sciences - ISCIS 2003. ISCIS 2003. Lecture Notes in Computer Science, vol 2869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39737-3_40
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DOI: https://doi.org/10.1007/978-3-540-39737-3_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20409-1
Online ISBN: 978-3-540-39737-3
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