Parallel Clustering of Gene Expression Dataset in Multicore Environment
Clustering has become the powerful and widely used method in gene expression dataset analysis to obtain biological information. Clustering using sequential approach is time consuming task. So as to save time and to increase speedup we have applied parallel clustering on single machine utilizing computational power of multicore processors in the system. In this work, we have also done comparison of sequential clustering and the parallel clustering in terms of time consumed for clustering of yeast gene expression dataset. With the use of multicore processor the speedup gained from 5 to 7% on intel core 2 duo processor with 2Gb RAM.