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Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges

文献类型：期刊论文

作者Yin, Zekun2; Lan, Haidong2; Tan, Guangming3; Lu, Mian4; Vasilakos, Athanasios V.1; Liu, Weiguo2
刊名COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
出版日期2017
卷号15页码:403-411
关键词Computational biology applications Computing platforms Big biological data NGS GPU Intel MIC
ISSN号2001-0370
DOI10.1016/j.csbj.2017.07.004
英文摘要The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics. (C) 2017 The Authors. Published by Elsevier B.V.
WOS研究方向Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology
语种英语
WOS记录号WOS:000425900600030
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/6150]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Liu, Weiguo
作者单位1.Lulea Univ Technol, Dept Comp Sci Elect & Space Engn, SE-93187 Skelleftea, Sweden
2.Shandong Univ, Jinan, Shandong, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
4.Huawei Singapore Res Ctr, Singapore, Singapore
推荐引用方式
GB/T 7714		 Yin, Zekun,Lan, Haidong,Tan, Guangming,et al. Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges[J]. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,2017,15:403-411.
APA Yin, Zekun,Lan, Haidong,Tan, Guangming,Lu, Mian,Vasilakos, Athanasios V.,&Liu, Weiguo.(2017).Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,15,403-411.
MLA Yin, Zekun,et al."Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges".COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL 15(2017):403-411.

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来源：计算技术研究所

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