Now and Next-Generation Sequencing Techniques: Future of Sequence Analysis Using Cloud Computing - Thakur, Radhe S.; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav (Frontiers in Genetics, 2012)
Advancements in the field of sequencing techniques resulted in the huge sequenced data to be produced at a very faster rate. It is going cumbersome for the datacenter to maintain the databases. Data mining and sequence analysis approaches needs to analyze the databases several times to reach any efficient conclusion. To cope with such overburden on computer resources and to reach efficient and effective conclusions quickly, the virtualization of the resources and computation on pay as you go concept was introduced and termed as cloud computing. The datacenter’s hardware and software is collectively known as cloud which when available publicly is termed as public cloud. The datacenter’s resources are provided in a virtual mode to the clients via a service provider like Amazon, Google and Joyent which charges on pay as you go manner. The workload is shifted to the provider which is maintained by the required hardware and software upgradation. The service provider manages it by upgrading the requirements in the virtual mode. Basically a virtual environment is created according to the need of the user by taking permission from datacenter via internet, the task is performed and the environment is deleted after the task is over. In this discussion, we are focusing on the basics of cloud computing, the prerequisites and overall working of clouds. Furthermore, briefly the applications of cloud computing in biological systems, especially in comparative genomics, genome informatics and SNP detection with reference to traditional workflow are discussed.