Department of Bioscience and Biotechnology, Banasthali University, Banasthali, Rajasthan, India.
OMICS. 2012 Jul-Aug;16(7-8):422-8. doi: 10.1089/omi.2012.0001. Epub 2012 Jun 26.
High-throughput genome research has long been associated with bioinformatics, as it assists genome sequencing and annotation projects. Along with databases, to store, properly manage, and retrieve biological data, a large number of computational tools have been developed to decode biological information from this data. However, with the advent of next-generation sequencing (NGS) technology the sequence data starts generating at a pace never before seen. Consequently researchers are facing a threat as they are experiencing a potential shortage of storage space and tools to analyze the data. Moreover, the voluminous data increases traffic in the network by uploading and downloading large data sets, and thus consume much of the network's available bandwidth. All of these obstacles have led to the solution in the form of cloud computing.
高通量基因组研究长期以来一直与生物信息学相关联,因为它有助于基因组测序和注释项目。除了数据库用于存储、妥善管理和检索生物数据外,还开发了大量计算工具来从这些数据中解码生物信息。然而,随着下一代测序(NGS)技术的出现,序列数据的生成速度前所未有。因此,研究人员面临着一个威胁,因为他们面临着存储空间和数据分析工具的潜在短缺。此外,大量数据通过上传和下载大数据集增加了网络流量,从而消耗了网络可用带宽的很大一部分。所有这些障碍都导致了云计算的解决方案。