A clustering algorithm based on generalized similarity for co-regulated genes

A novel clustering model, i.e., the g-Cluster, is developed on the basis of generalized similarity for the special properties and disadvantages of existing clustering algorithms of co-regulated genes. The positive and negative co-regulated genes in this model are integrated into the same cluster if and only if they are provided with the same code. Further, a tree-based clustering algorithm FBTD (first breadth then depth) is proposed, where the priorities in search strategy is that the breadth is taken first then the depth, to find out all the maximal g-Clusters with high-efficiency pruning rules and optimizing strategy performed simultaneously. Applying the FBTD algorithm to real datasets involving genes, both the theoretic and testing results showed that the algorithm is practically efficient.