A survey of life sciences applications on the grid

The availability of powerful microprocessors and improvements in the performance of networks has enabled high performance computing on wide-area, distributed systems. Computational grids, by integrating diverse, geographically distributed and essentially heterogeneous resources provide the infrastructure for solving large-scale problems. However, heterogeneity, on the one hand allows for scalability, but on the other hand makes application development and deployment for such an environment extremely difficult. The field of life sciences has been an explosion in data over the past decade. The data acquired needs to be processed, interpreted and analyzed to be useful. The large resource needs of bioinformatics allied to the large number of data-parallel applications in this field and the availability of a powerful, high performance, computing grid environment lead naturally to opportunities for developing grid-enabled applications. This survey, done as part of the Life Sciences Research Group (a research group belonging to the Global Grid Forum) attempts to collate information regarding grid-enabled applications in this field. Arun Krishnan, Ph.D.: He did his undergraduate in Electrochemical Engineering in the Central Electrochemical Research Institute in India and went on to do his Ph.D. in Advanced Process Control from the University of South Carolina. He then worked in the control and high performance computing industries for about 3 years before moving to the Bioinformatics Institute in Singapore. He is currently a Young Investigator for the Distributed Computing in Biomedicine Group at BII. His research interests include parallel and distributed computing with special emphasis on grid computing and its application to the biomedical area. He is also interested in developing parallel algorithms for sequence analysis and protein structure prediction.