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A biclustering algorithm with coherent evolution on the contiguous columns facing time-series gene data

Biclustering technique has become an important tool in analysis of gene expression data. However, most traditional biclustering algorithms focus on biclustering model on non-continuous column. For time series gene expression data, these models neglect the important internal sequential relationship between the time intervals, thus it is not suitable for this kind of data. This paper proposes an effective and exact algorithm, which can be used to mine biclusters with coherent evolution on the contiguous columns on time series gene expression data. The experimental results show that the algorithm can find biclusters of statistical significance and rather strong biological relevance.