In the last years a large amount of information about genomes was discovered, increasing the complexity of analysis. Therefore the most advanced techniques and algorithms are required. In many cases researchers use unsupervised clustering. But the inability of clustering to solve a number of tasks requires new algorithms. So, recently, scientists turned their attention to the biclustering techniques. In this paper we propose a novel biclustering technique, that we call Combinatorial Biclustering Algorithm (BCA). This technique permits to solve the following problems: 1) classification of data with respect to rows and columns together; 2) discovering of the overlapped biclusters; 3) definition of the minimal number of rows and columns in biclusters; 4) finding all biclusters together. We apply our model to two synthetic and one real biological data sets and show the results.
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