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      • Department of Molecular Biology and Genetics
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      Bi-k-bi clustering: mining large scale gene expression data using two-level biclustering

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      Author
      Çarkacioǧlu, L.
      Atalay, R.
      Konu, O.
      Atalay, V.
      Can, T.
      Date
      2010
      Source Title
      International Journal of Data Mining and Bioinformatics
      Print ISSN
      1748-5673
      Publisher
      Inderscience Enterprises Ltd.
      Volume
      4
      Issue
      6
      Pages
      701 - 721
      Language
      English
      Type
      Article
      Item Usage Stats
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      Abstract
      Due to the increase in gene expression data sets in recent years, various data mining techniques have been proposed for mining gene expression profiles. However, most of these methods target single gene expression data sets and cannot handle all the available gene expression data in public databases in reasonable amount of time and space. In this paper, we propose a novel framework, bi-k-bi clustering, for finding association rules of gene pairs that can easily operate on large scale and multiple heterogeneous data sets. We applied our proposed framework on the available NCBI GEO Homo sapiens data sets. Our results show consistency and relatedness with the available literature and also provides novel associations. Copyright © 2010 Inderscience Enterprises Ltd.
      Keywords
      APD
      Association pattern discovery
      Biclustering
      Gene expression analysis
      Spearman rank correlation
      Permalink
      http://hdl.handle.net/11693/22099
      Published Version (Please cite this version)
      http://dx.doi.org/10.1504/IJDMB.2010.037548
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