Hi. The clustering algorithms present in R assume i have a data matrix. However my data is expressed as a graph (nodes and weights between these nodes). Generally i can work around this by replacing the weights as similarities in the dissimilarity matrix, but as R clustering algorithms like MClust work from the original data matrix i cant do this in this case. Is there any way i could obtain a suitable matrix to replace the data matrix starting just from the knowledge i have from the graph? I have no idea if this is even mathematically feasible as you seem to lose information when going from the data matrix to the dissimilarity matrix. Well, thanks [[alternate HTML version deleted]]