Cloud computing: Applications in biological research and future prospects

Cloud computing, providing access to more than a hundred thousand computers at a time to process, store or share information has stretched the horizon of possibilities in many areas of science and business. The pay as you use nature of cloud computing services such as EC2 provided by Amazon wherein you pay only for the servers, server or part thereof that you use also makes it economically attractive. This paper is targeted at researchers in the field of genetics and biotechnology who wish to understand how cloud computing can contribute to their area of research. Bio-informatics tools are extensively used in biological research today. These tools can be utilized more efficiently and in a possibly more cost and time effective manner using cloud technology. High-throughput genomics leads to reams of data that cannot be processed by local research facility computers at the speed it is generated. This bottleneck has been overcome by the use of cloud computing to store and to process data in real time. Large datasets and applications for image analysis, data mining, protein folding, and gene sequencing can also be shared for collaborative research between facilities using clouds. This is a simpler approach than transferring such data. Clouds also provide applications such as Apache's Hadoop and Google's MapReduce for parallel computing (particularly useful for making services such as BLAST easier to deploy in a shorter time). Cloud computing with characteristics like multi-tenacity, scalability, low cost, virtualization, agility and empowerment of end users has made it possible to share the results of studies at much finer granularity, along with sharing scientific investigations at the level of individual data points. Cloud technology can contribute significantly in areas such as biodiversity informatics and the study of human genetic variation and disease. We discuss these possibilities, the challenges in realizing the potential for application of cloud technology in biological sciences, and the work being done to overcome these challenges.