Abstract:

The high throughput technologies (microarrays, next generation sequencing…) have become a powerful tool for functional genomics. So analysis of gene expression data derived from these technologies is required to extract implicit and relevant knowledge about genes. But the large volume of gene expression data makes the extraction process more difficult. We need puissant algorithms that can mine large real data. In this paper, we cite some patterns extraction algorithms used in the literature to extract patterns from gene expression data. Furthermore, we choose to use Paraminer, a generic and parallel algorithm of patterns extraction. Then, we test this algorithm in our gene expression dataset to extract the relationships between genes