Maximal CCC-Biclusters and maximal e -CCC-Biclusters. This figure shows: (Top) 1-CCC-Biclusters obtained from the maximal CCC-Biclusters in Figure 2 by extending them with genes by looking for their approximate patterns in the generalized suffix tree (1-CCC-Biclusters B1_1, B2_1, B3_1, B5_1 and B6_1) or extending them with e = 1 contiguous columns at right (1-CCC-Biclusters B1_2, B1_3, B2_2, B4_2, B6_2 and B6_3) or at left (1-CCC-Biclusters B2_3, B3_2, B4_1, B5_2 and B5_3). Note that several of these 1-Biclusters can be defined by more than one expression pattern. This is the case of 1-CCC-Biclusters B2_1, B2_3, B3_2, B4_1 and B4_2, which in fact correspond to maximal 1-CCC-Biclusters (see Figure 5). Other 1-CCC-Biclusters are identified by a single expression pattern. This is the case of 1-CCC-Biclusters B1_1, B1_2, B2_1, B3_1, B5_1, B5_2, B6_1 and B6 2, and also correspond to maximal 1-CCC-Biclusters (see Figure 5). However, the 1-CCC-Biclusters B1_3, B5_3 and B6_3 do not correspond to maximal 1-CCC-Biclusters since they are not row-maximal. (Bottom) Maximal 1-CCC-Biclusters B1_3, B5_3 and B6_3 obtained not only by extending maximal CCC-Biclusters B1, B5 and B6 with one contiguous column to the right, left and right, respectively, but also by looking for the patterns in the 1-neighborhood of the patterns SB 1_3= [U U] (columns C1–C2), SB 5_3= [U U] (columns C4–C5) and SB 6_3= [N U] (columns C1–C2). Note however, that even if we replaced the non maximal 1-CCC-Biclusters B1_3, B5_3 and B6_3 (in the top) by the truly maximal 1-CCC-Biclusters (in the bottom) we could only find 16 of the 36 maximal 1-CCC-Biclusters with at least two rows shown in Figure 5 that can be found in the discretized matrix in Figure 1.