Catálogo de publicaciones - libros

Open Grid Service Architecture - Data Access and Integration (OGSA-DAI) is a middleware which aims to provide a unique interface to heterogeneous database management systems and to special type of files like SwissProt files. It could become a vital tool for data integration in life sciences since the data is produced by different sources and residing in different data management systems. With it, users will have more flexibility in accessing the data than using static interfaces of Web Services.

OGSA-DAI was tested to determine in which way it could be used efficiently in a Grid application called RNAi screening. It was evaluated in accessing data from bio-databases using the queries that a potential user of RNAi screening would execute. The observations show that OGSA-DAI has some considerable overhead compared to a JDBC connection but provides additional features like security which in turn are very important for distributed processing in life sciences.

Microarray experiments can provide molecular-level insight into a variety of biological processes, from yeast cell cycle to tumorogenesis. However, analysis of both genomic and protein microarray data requires interactive collaborative investigation by biology and bioinformatics researchers. To assist collaborative analysis, remote collaboration tools for integrative analysis and visualization of microarray data are necessary. Such tools should: (i) provide fast response times when used with visualization-intensive genomics applications over a low-bandwidth wide area network, (ii) eliminate transfer of large and often sensitive datasets, (iii) work with any analysis software, and (iv) be platform-independent. Existing visualization systems do not satisfy all requirements. We have developed a remote visualization system called Varg that extends the platform-independent remote desktop system VNC with a novel global compression method. Our evaluations show that the Varg system can support interactive visualization-intensive genomic applications in a remote environment by reducing bandwidth requirements from 30:1 to 289:1.

This paper proposes High Voltage Electron Microscope (HVEM) DataGrid for biological data management. HVEM DataGrid allows researchers to share the results of their biological experiments using HVEM, so that they can analyze them together to perform good research. The proposed system is for people whose primary work is to access HVEM, to obtain experimental results for biological samples and to store or retrieve them on HVEM DataGrid. The architecture of the HVEM Grid[3] is designed to materialize all the necessary conditions in allowing the user 1) to control every part of HVEM in a fine-grained manner, 2) to check the HVEM and observe various states of the specimen, 3) to manipulate their high resolution 2-D and 3-D images, and 4) to handle the experimental data including storing and searching them. HVEM DataGrid, a subsystem of the HVEM Grid system, is to provide a simple web-based controlling method for remote biological data.