Big data in biology: The hope and present-day challenges in it
Big data in biology: The hope and present-day challenges in it
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DOI：
10.1016/j.genrep.2020.100869
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发表时间：
2020-12-01
期刊：
影响因子：
1.3
通讯作者：
Ghosh, Zhumur
中科院分区：
文献类型：
--
作者：
Pal, Subhajit;Mondal, Sudip;Ghosh, Zhumur
新技术的浪潮为经济有效地生成生物系统的高通量概况提供了机会。这产生了大量的生物数据。因此，它正引领我们走向“大数据”时代，这迫切需要弥合高通量技术发展与我们管理、分析和整合生物大数据的能力之间的差距。为了最大限度地利用它，需要为大数据管理和分析开发足够的专业知识。在这篇综述中，我们讨论了与非结构化和结构化生物大数据的存储，传输，访问和分析相关的挑战。随后，它提供了关于生物大数据管理所采用的重要策略的全面总结，其中包括讨论所有最近使用的工具或软件，用于生物大数据的高通量处理和分析。最后讨论了大数据生物信息学的未来前景。
The wave of new technologies has opened up the opportunity for cost-effective generation of high-throughput profiles of biological systems. This is generating tons of biological data. It is thus leading us towards the "big data" era which is creating a pressing need to bridge the gap between high-throughput technological development and our ability for managing, analyzing, and integrating the biological big data. To harness the maximum out of it, sufficient expertise needs to be developed for big data management and analysis. In this review, we discuss the challenges related to storage, transfer, access and analysis of unstructured and structured biological big data. Subsequently, it provides a comprehensive summary regarding the important strategies adopted for biological big data management which includes a discussion on all the recently used tools or software built for high throughput processing and analysis of biological big data. Finally it discusses the future perspectives of big data bioinformatics.