Title: A cube framework for incorporating inter-gene information into biological data mining

Authors: Kuan-ming Lin, Jaewoo Kang, Hanjun Shin, Jusang Lee

Addresses: Department of Computer Science, Duke University, Durham, North Carolina 27708, USA. ' Department of Computer Science and Engineering, College of Information and Communication, Korea University, Anam-Dong, Seongbuk-Gu, Seoul 136-705, Korea. ' Department of Computer Science and Engineering, College of Information and Communication, Korea University, Anam-Dong, Seongbuk-Gu, Seoul 136-705, Korea. ' Department of Computer Science and Engineering, College of Information and Communication, Korea University, Anam-Dong, Seongbuk-Gu, Seoul 136-705, Korea

Abstract: Large volumes of microarray data are registered daily in public repositories such as SMD (Belkin and Niyogi, 2003) and GEO (Ashburner et al., 2000). Such repositories have quickly become a community resource. However, due to the inherent heterogeneity of the microarray experiments, the data generated from different experiments could not be directly integrated and hence the resources have not been fully utilised. To address this problem, we propose a new microarray integration framework that achieves high-quality integration through exploiting invariant features such as relative information among genes. We also show how the proposed approach generalises the previous frameworks.

Keywords: inter-gene analysis; cube framework; TSP; top-scoring pair; second-order correlation; data mining; bioinformatics; microarray data; microarray integration; data integration.

DOI: 10.1504/IJDMB.2009.023881

International Journal of Data Mining and Bioinformatics, 2009 Vol.3 No.1, pp.3 - 22

Published online: 17 Mar 2009 *

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