Towards BIMAX: Binary Inclusion-MAXimal Parallel Implementation for Gene Expression Analysis Alejandra

Abstract

Differential gene expression analysis and clustering techniques have been current tools to study the relation between a gene and biological processes. Since a group of genes may show co-expression under certain conditions, biclustering techniques have been used to find sets of genes sharing similar expression patterns. We present an analysis of the performance of the BIMAX: Binary Inclusion-MAXimal sequential biclustering algorithm. Its performance is evaluated using synthetic datasets. Finally, we propose a strategy of parallelization for optimizing the performance of the BIMAX using parallel programming techniques.