2012

Conférence

DEXA Workshops 2012: 206-210

Microarrays represent a new technology for measuring expression levels of several genes under various biological conditions generating multiple data. These data can be analyzed by using biclustering method which aims to extract a maximum number of genes and conditions presenting a similar behavior. This paper proposes a new evolutionary approach to obtain maximal high-quality biclusters of highly-correlated genes. The performance of the proposed algorithm is assessed on synthetic gene expression data. Experimental results show that our algorithm competes favorably with several state-of-the-art biclustering algorithms.

@INPROCEEDINGS{Ayadi2012Dexa,
author={Ayadi, Wassim and Maâtouk, Ons and Bouziri, Hend},
booktitle={2012 23rd International Workshop on Database and Expert Systems Applications},
title={Evolutionary Biclustering Algorithm of Gene Expression Data},
year={2012},
pages={206-210},
doi={10.1109/DEXA.2012.46}}