We describe an initial implementation of a platform for the analysis of gene promoter architecture for sets of genes from human and other higher organisms, using NorduGrid as the Grid Virtual Organization. The procedure leading from a set of co-regulated genes to a set of inferred common regulatory elements involves a number of computationally intensive, but well scalable steps. We show it is feasible to implement a high performance genomic regulatory sequence analysis pipeline on the Grid with minimal modification to the existing computational biology software components. We applied a job binning step to dramatically reduce the overhead for submitting a set of many small jobs to the Grid. Even with simple jobs and a relatively small size of the Grid, we observed up to 25-fold performance improvement over a comparable or more powerful single or dual-CPU platform. Our implementation of biological sequence alignment and transcription factor binding site algorithms on the Grid proves that even simple applications can take advantage of computational resources that adopted this computational paradigm.

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