Gene Function Prediction Using Improved Fuzzy c-Means Algorithm

Currently, there are many new discoveries of gene expression analysis. In order to analyze the gene expression data, fuzzy clustering algorithms are widely used. However, common clustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biological process, molecular function, and cellular component, and were not tested with different functional annotation database formats. Furthermore, the common clustering algorithms do not provide the information of dominant gene among the clusters. In this paper, we present a new computational framework for clustering gene expression data. From this experiment, we can conclude that our framework capable of determining the dominant gene and also predict the unknown genes.