@inproceedings{db8748d1335c4254a7d1b436962118a7,
title = "Microarray biclustering with crowding based MOACO",
abstract = "Biclustering methods allow us to identify genes with similar behavior with respect to different conditions. Ant Colony Optimization (ACO) algorithms have been shown to be effective problem solving strategies for Multiple Objective Optimization (MOO). Multiple Objective Ant colony optimization (MOACO) mainly focuses on solving the multiple objective combinatorial optimization problems. This paper incorporates crowding update technology into MOACOB and proposes a novel crowding based MOACO biclustering algorithm to mine biclusters from microarray dataset. Experimental results are shown for biclustering algorithm on two real gene expression dataset.",
author = "Junwan Liu and Zhoujun Li and Xiaohua Hu and Yiming Chen",
year = "2009",
doi = "10.1109/BIBM.2009.23",
language = "英语",
isbn = "9780769538853",
series = "2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009",
pages = "170--173",
booktitle = "2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009",
note = "2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 ; Conference date: 01-11-2009 Through 04-11-2009",
}