Signal finding (pattern discovery) in biological sequences is a fundamental problem in both computer science and molecular biology. Many approaches have been proposed for extracting interesting patterns (or motifs) from DNA/RNA and protein sequences. Some approaches are based on simple and multiple alignment techniques, some use biological knowledge and others do not. In this paper, we propose a de novo framework that performs motifs identification and exploits a constrained coclustering technique allowing one to simultaneously find associations between groups of protein sequences and groups of motifs . We show that the presented approach is able to group together protein sequences belonging to the same families and, at the same time to provide a set of characterizing motifs. Categories and Subject Descriptors J.3 [Computer Applications]: Life and Medical Sciences; I.5.3 [Computing Methodologies]: Pattern Recognition— Clustering Keywords Protein motif, Pattern discovery, Constrai...