Classification of gene functions using support vector machine for time-course gene expression data
作者： Changyi Park , Ja-Yong Koo , Sujong Kim , Insuk Sohn , Jae Won Lee
DOI: 10.1016/J.CSDA.2007.09.002
关键词:
摘要: Since most biological systems are developmental and dynamic, time-course gene expression profiles provide an important characterization of functions. Assigning functions for genes with unknown based on expressions is task in functional genomics. Recently, various methods have been proposed the classification data. In this paper, we consider from data analysis viewpoint, where a support vector machine adopted. The can model temporal effects by incorporating coefficients as well basis matrix obtained finite expansion set We apply to both real microarray simulated Our results indicate that effective discriminating predefined method also provides valuable information about interactions between allows assignment new
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