Parallel Computing - Special issue: High-performance parallel bio-computing
A case study of parallel I/O for biological sequence search on Linux clusters
International Journal of High Performance Computing and Networking
An integrated statistical comparative analysis between variant genetic datasets of Mus musculus
International Journal of Computational Intelligence in Bioinformatics and Systems Biology
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Thanks to the development of genetic engineering, various kinds of genomic information are being unveiled.Hence, it becomes feasible to analyze the entire genomicinformation all at once. On the other hand, the quantity ofthe genomic information stocked on databases is increasingday after day. In order to process the whole information, wehave to develop an effective method to deal with lots of data.Therefore, it is indis ensable not only to make an effectiveand rapid algorithm but also to use high-speed computerresource so as to analyze the biological information. Forthis purpose, as one of the most promised computing environments, the grid computing architecture has appearedrecently. The European Data Grid (EDG) is one of the data-oriented grid computing environments [11].In the field of bioinformatics, it is important to findunique sequences to succeed in molecular biological experiments [6]. Once unique sequences have been found, theycan be useful for target specific probes/primers design, genesequence comparison and so on. In this paper, we propose amethod to discover unique sequences from among genomicdatabases located in a distributed environment. Next, weimplement this method upon the European Data Grid andshow the calculation results for E. coli genomes.