Development of an information platform for new grid users in the biomedical field

Bringing new users into grids is a top priority for all grid initiatives and one of the most challenging tasks. Especially in life sciences it is essential to have a certain amount of users to establish a critical mass for a sustainable grid and give feedback back to the technological middleware layer. Based on the presumable lack of grid IT knowledge it is notably more arduous to satisfy user demands although here the requirements are especially demanding. Therefore, the development of an information- and learning platform could support the efforts of grid experts to guide new users. By providing a platform about grid technology and their feasibilities for users of the community of biomedicine potential, users could be supported using the high potential of their discipline

Development of an information platform for new grid users in the biomedical field

Bringing new users into grids is a top priority for all grid initiatives and one of the most challenging tasks. Especially in life sciences it is essential to have a certain amount of users to establish a critical mass for a sustainable grid and give feedback back to the technological middleware layer. Based on the presumable lack of grid IT knowledge it is notably more arduous to satisfy user demands although here the requirements are especially demanding. Therefore, the development of an information- and learning platform could support the efforts of grid experts to guide new users. By providing a platform about grid technology and their feasibilities for users of the community of biomedicine potential, users could be supported using the high potential of their discipline

Innovative in silico approaches to address avian flu using grid technology

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper presents how we are currently exploring how to integrate the existing data sources towards a global surveillance network for molecular epidemiology.Comment: 7 pages, submitted to Infectious Disorders - Drug Target

Towards data grids for microarray expression profiles

The UK DTI funded Biomedical Research Informatics Delivered by Grid Enabled Services (BRIDGES) project developed a Grid infrastructure through which research into the genetic causes of hypertension could be supported by scientists within the large Wellcome Trust funded Cardiovascular Functional Genomics project. The BRIDGES project had a focus on developing a compute Grid and a data Grid infrastructure with security at its heart. Building on the work within BRIDGES, the BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project plans to provide an enhanced data Grid infrastructure to support richer queries needed for the discovery and analysis of microarray data sets, also based upon a fine-grained security infrastructure. This paper outlines the experiences gained within BRIDGES and outlines the status of the GEMEPS project, the open challenges that remain and plans for the future

Applications of the ACGT Master Ontology on Cancer

In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the ontology within the ACGT project thus far