UniBic: Sequential row-based biclustering algorithm for analysis of gene expression data.

To identify a significant trend-preserving bicluster, we have to get those remaining original rows and their negative ones involved in the row extension process by repeatedly adding new rows (original or negative) one at a time with an error rate ≤0.15 until none is available.

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