A Novel Clustering Algorithm for Biological Data

Clustering analysis has become a valuable and useful tool for biological data. In recent years, a number of clustering algorithms have been developed. However, they are confronted with difficulties in meeting the requirements of automation, quality and robustness at the same time. In this paper, we propose a clustering algorithm that can tackle some of these problems. The algorithm has been tested extensively on synthetic as well as real world biological data sets. The experimental results demonstrate that the proposed algorithm is very effective in producing desired clusters of the given data sets.