Journal
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
Volume 4, Issue 6, Pages 701-721Publisher
INDERSCIENCE ENTERPRISES LTD
DOI: 10.1504/IJDMB.2010.037548
Keywords
biclustering; APD; association pattern discovery; Spearman rank correlation; gene expression analysis
Categories
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available