2008 IdentifyingBiologicallyRelevant

(Zhao et al., 2008) ⇒ Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, and Yung Chang. (2008). “Identifying Biologically Relevant Genes via Multiple Heterogeneous Data Sources.” In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2008). doi:10.1145/1401890.1401990

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Abstract

Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioinformatics has made various data sources available such as mRNA and miRNA expression profiles, biological pathway and gene annotation, etc. Efficient and effective integration of multiple data sources helps enrich our knowledge about the involved samples and genes for selecting genes bearing significant biological relevance. In this work, we studied a novel problem of multi-source gene selection: given multiple heterogeneous data sources (or data sets), select genes from expression profiles by integrating information from various data sources. We investigated how to effectively employ information contained in multiple data sources to extract an intrinsic global geometric pattern and use it in covariance analysis for gene selection. We designed and conducted experiments to systematically compare the proposed approach with representative methods in terms of statistical and biological significance, and showed the efficacy and potential of the proposed approach with promising findings.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 IdentifyingBiologicallyRelevant	Huan Liu Jieping Ye Zheng Zhao Jiangxin Wang Yung Chang			Identifying Biologically Relevant Genes via Multiple Heterogeneous Data Sources				10.1145/1401890.1401990