On the Complexity and Completeness of Robust Biclustering Algorithm (ROBA)

A biclustering algorithm named ROBA has been used in a number of recent works. We present a time and space efficient implementation of ROBA that reduces the time and space complexity by an order of L where L is the number of distinct values present in the data. Our implementation runs almost 11 times faster than the existing implementation on Yeast gene expression dataset. We also improve ROBA and then use it to present an iterative algorithm that can find all perfect biclusters with constant values, constant values on rows and constant values on columns. Though our algorithm may take exponential time in the worst case, we use some subtle observations to reduce computational time and space. Experimental result reveals that our algorithm runs in reasonable time on Yeast gene expression dataset and finds almost 10 times more biclusters than ROBA.