Application of data mining techniques to protein-protein interaction prediction

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dc.citation.epage323en_US
dc.citation.spage316en_US
dc.citation.volumeNumber2869en_US
dc.contributor.authorKocatas, A.en_US
dc.contributor.authorGursoy, A.en_US
dc.contributor.authorAtalay, R.en_US
dc.date.accessioned2016-02-08T10:28:47Z
dc.date.available2016-02-08T10:28:47Z
dc.date.issued2003en_US
dc.departmentDepartment of Molecular Biology and Geneticsen_US
dc.description.abstractProtein-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. © Springer-Verlag Berlin Heidelberg 2003.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:28:47Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2003en
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11693/24397
dc.language.isoEnglishen_US
dc.publisherSpringer-Verlag Berlinen_US
dc.source.titleLecture Notes in Computer Scienceen_US
dc.titleApplication of data mining techniques to protein-protein interaction predictionen_US
dc.typeArticleen_US

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