Abstract
Biclustering is an important analysis method on gene expression data. However, few biclustering methods provided a query-based approach for biologists to search the biclusters which contain a certain gene of interest. In this paper, we proposed a generalized fuzzy-based approach, namely Weighted Fuzzy-based Maximum Similarity Biclustering (WF-MSB), for extracting a query-based bicluster based on the user-defined reference gene. A fuzzy-based similarity measurement and condition weighting approach are used to extract significant most similar and most dissimilar biclusters to the reference gene in expression levels. The proposed WF-MSB method was evaluated in comparison with MSBE on a real yeast microarray data, and the results show that WF-MSB can effectively find the biclusters with significant GO-basedfunctional meanings.
