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As a high-throughput detection technology, the gene chips produce huge amount of gene expression data. How to effectively analyze the data has become an urgent need. Biclustering techniques have been used as important tools to find the local patterns in gene expression data. Biclustering is to find submatrices, so that a subset of the genes shows a “highly correlated behavior in a subset of conditions”...
Most traditional biclustering algorithms focus on biclustering model on non-continuous column, which are not suitable for the analysis of the time series gene expression data. We proposes an effective and exact algorithm, which can be used to mine biclusters with coherent evolution on the contiguous columns as well as the complementary biclusters and time-lagged biclusters for the analysis of time...
Biclustering algorithm is used to find local patterns as an important tool in the analysis of gene expression data. However, most of the biclusters found by existing biclustering algorithms consist of non-continuous columns. It is not suitable for time series gene expression data, which has not been extensively studied. This paper presents an efficient exact algorithm to search contiguous column coherent...
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