WISDOM: A Grid-Enabled Drug Discovery Initiative Against Malaria

The goal of this chapter is to present the WISDOM initiative, which is one of the main accomplishments in the use of grids for biomedical sciences achieved on grid infrastructures in Europe. Researchers in life sciences are among the most active scientifi c communities on the EGEE infrastructure. As a consequence, the biomedical virtual organization stands fourth in terms of resources consumed in 2007, with an average of 7000 jobs submitted every day to the grid and more than 4 million hours of CPU consumed in the last 12 months. Only three experiments on the CERN Large Hadron Collider have used more resources. Compared to particle physics, the use of resources is much less centralized as about 40 different scientifi c applications are now currently deployed on EGEE. Each of them requires an amount of CPU which ranges from a few to a few hundred CPU years. Thanks to the 20,000 processors available to the users of the biomedical virtual organization, crunching factors in the hundreds are witnessed routinely. Such performances were already achieved on supercomputers but at the cost of reservation and long delays in the access to resources. On the contrary, grid infrastructures are constantly open to the user communities. Such changes in the scale of the computing resources made continuously available to the researchers in biomedical sciences open opportunities for exploring new fi elds or changing the approach to existing challenges. In this chapter, we would like to show the potential impact of grids in the fi eld of drug discovery through the example of the WISDOM initiative

Finding unique PCR products on distributed databases

Thanks to the development of genetic engineering, various kinds of genomic information are being unveiled. Hence, now, it becomes feasible to study in molecular biology by analyzing the entire genomic information. On the other hand, the quantity of the genomic information stocked in database is increasing day after day. In order to process the whole information, we have to develop an effective method to deal with lots of data. It is indispensable not only to make an effective and rapid algorithm but also to use high-speed computer resource so as to analyze the biological information. For this purpose, as one of the most promised computing environments, the grid computing architecture has appeared recently. The European Data Grid (EDG) is one of the grid com-puting environments. In the first stage of designing hybridization probes and PCR primers, it is extremely important to find genuinely unique sequence on a target genome. We deployed a novel method to design PCR primers, which takes into account not only the specificity of the primer itself but also the uniqueness of the product length. In this paper, we improve our proposed method to find unique PCR products on distributed databases. We show also the sequences found by our method, which can not be uniquely observed by any probe sequence but by a pair of PCR primers on S. cerevisiae genome. 1

Partitionning medical image databases for content-based queries on a grid

articleInternational audienceIn this article we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned in subsets to be processed on different grid nodes. A theoretical model of the application computation cost and estimates of the grid execution overhead are used to efficiently partition the database. We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time