Bi-k-bi clustering: mining large scale gene expression data using two-level biclustering
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, cilt.4, sa.6, ss.701-721, 2010 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 4 Sayı: 6
- Basım Tarihi: 2010
- Doi Numarası: 10.1504/ijdmb.2010.037548
- Dergi Adı: INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.701-721
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
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.