Data Management and Analysis Architecture for a More Efficient and Productive Bioinformatics Environment

Bioinformaticians should not concern themselves with problems related to computing technologies, and only focus on analysis of biological data. In reality, however, they need to know quite a bit about computer hardware, networking, robotics, image processing, and many others that affect the collection, storage, analysis, and distribution of biological information. Computing technologies enable bioinformtics effectively only if proper management of data and computational resources accompanies their deployments. Bioinformatics organizations - pharmaceutical companies, biotechnology firms, research institutions and the like - need an IT infrastructure that can handle vast, heterogeneous data produced internally or acquired from third parties, and manage diverse computational resources. The goal is to provide scientists with the data and computational resources they need in the right forms on-demand, relieving them from attending to IT issues. This paper describes an architecture that leverages current technologies for bioinformatics data management and analysis to minimize scientists´ involvements in the IT minutia, in order to achieve a more efficient and productive bioinformatics environment.