A bioinformatics knowledge discovery in text application for grid computing

<p>Abstract</p> <p>Background</p> <p>A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources.</p> <p>Methods</p> <p>The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs.</p> <p>Results</p> <p>A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed.</p> <p>Conclusion</p> <p>In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities.</p

Large Scale In Silico Screening on Grid Infrastructures

Large-scale grid infrastructures for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale in silico docking within the framework of the WISDOM initiative against Malaria and Avian Flu requiring about 105 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large-scale grid infrastructures for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large-scale deployment.Comment: 14 pages, 2 figures, 2 tables, The Third International Life Science Grid Workshop, LSGrid 2006, Yokohama, Japan, 13-14 october 2006, to appear in the proceeding

User oriented access to secure biomedical resources through the grid

The life science domain is typified by heterogeneous data sets that are evolving at an exponential rate. Numerous post-genomic databases and areas of post-genomic life science research have been established and are being actively explored. Whilst many of these databases are public and freely accessible, it is often the case that researchers have data that is not so freely available and access to this data needs to be strictly controlled when distributed collaborative research is undertaken. Grid technologies provide one mechanism by which access to and integration of federated data sets is possible. Combining such data access and integration technologies with fine grained security infrastructures facilitates the establishment of virtual organisations (VO). However experience has shown that the general research (non-Grid) community are not comfortable with the Grid and its associated security models based upon public key infrastructures (PKIs). The Internet2 Shibboleth technology helps to overcome this through users only having to log in to their home site to gain access to resources across a VO – or in Shibboleth terminology a federation. In this paper we outline how we have applied the combination of Grid technologies, advanced security infrastructures and the Internet2 Shibboleth technology in several biomedical projects to provide a user-oriented model for secure access to and usage of Grid resources. We believe that this model may well become the de facto mechanism for undertaking e-Research on the Grid across numerous domains including the life sciences