Abstract. Biclustering, which can be defined as the simultaneous clus-tering of rows and columns in a data matrix, has received increasing attention in recent years, particularly in the field of Bioinformatics (e.g. for the analysis of microarray data). This paper proposes a novel biclus-tering approach, which extends the Affinity Propagation [1] clustering algorithm to the biclustering case. In particular, we propose a new ex-emplar based model, encoded as a binary factor graph, which allows to cluster rows and columns simultaneously. Moreover, we propose a li-near formulation of such model to solve the optimization problem using Linear Programming techniques. The proposed approach has been tested by using a well known synthetic microarray benchmark, with encouraging results. 1