M. Daoudi
ABSTRACT
Inferring gene regulatory network (GRN) is one of the major challenges in bioinformatics. A great amount of gene expression data is being produced raising the issue of GRN reconstruction. This later becomes an even more difficult task to perform when the biological dataset is very large. GRN reconstruction can be achieved through clustering. In this paper we propose a framework for gene expression data clustering for the purpose of GRN reconstruction. The proposed framework is based on a parallel BFR clustering using MapReduce programing model. Experimental results using several gene expression datasets from the literature show the effectiveness of the proposed framework
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