A Grid Framework to enable parallel and concurrent TMA image analyses

The Grid represents a great opportunity for the scientific community to solve computing intensive problems and share data. To actually allow its use, it is necessary to provide specific tools and enable a simplified exploitation of Grid resources. We address these topics in bioinformatics community to process images obtained through Tissue MicroArray technique. We developed Grid Framework for Tissue Microarray Analysis, shortly GF4TMA, that allows the selection and the analysis of TMA images on the Grid. In particular, users can analyse several images concurrently, and analyses are performed in parallel using Parallel IMAGE processing GEnoa Library, shortly PIMA(GE)² Lib. Therefore GF4TMA enables two levels of parallelism, the scheduling and the parallelism of the analyses are hidden to the users. A particular emphasis is posed on the two levels of parallelism provided by GF4TMA, and its effectiveness is discussed simulating different scenarios in Grid.