2012

Journal

Knowl. Based Syst. 35: 224-234

Biclustering is a very useful tool for analyzing microarray data. It aims to identify maximal groups of genes which are coherent with maximal groups of conditions. In this paper, we propose a biclustering algorithm, called BiMine+, which is able to detect significant biclusters from gene expression data. The proposed algorithm is based on two original features. First, BiMine+ is based on the use of a new tree structure, called Modified Bicluster Enumeration Tree (MBET), on which biclusters are represented by the profile shapes of genes. Second, BiMine+ uses a pruning rule to avoid both trivial biclusters and combinatorial explosion of the search tree. The performance of BiMine+ is assessed on both synthetic and real DNA microarray datasets. Experimental results show that BiMine+ competes favorably with several state-of-the-art biclustering algorithms and is able to extract functionally enriched and biologically relevant biclusters.

@article{AYADI2012224,
author = {Wassim Ayadi and Mourad Elloumi and Jin Kao Hao},
title = {BiMine+: An efficient algorithm for discovering relevant biclusters of DNA microarray data},
journal = {Knowledge-Based Systems},
volume = {35},
pages = {224-234},
year = {2012},
issn = {0950-7051},
doi = {https://doi.org/10.1016/j.knosys.2012.04.017},
url = {https://www.sciencedirect.com/science/article/pii/S095070511200113X}
}