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

Angélica Alejandra Serrano Rubio, Amilcar Meneses Viveros, Guillermo B. Morales Luna, Mireya Paredes López


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.


Biclustering, clustering, gene expression, high-performance computing, parallelism

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