Institute of Computing Technology, Chinese Academy IR
Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges | |
Yin, Zekun1; Lan, Haidong1; Tan, Guangming2; Lu, Mian3; Vasilakos, Athanasios V.4; Liu, Weiguo1 | |
2017 | |
发表期刊 | COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL |
ISSN | 2001-0370 |
卷号 | 15页码:403-411 |
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. |
关键词 | Computational biology applications Computing platforms Big biological data NGS GPU Intel MIC |
DOI | 10.1016/j.csbj.2017.07.004 |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology |
WOS类目 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology |
WOS记录号 | WOS:000425900600030 |
出版者 | ELSEVIER SCIENCE BV |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/6151 |
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.Shandong Univ, Jinan, Shandong, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.Huawei Singapore Res Ctr, Singapore, Singapore 4.Lulea Univ Technol, Dept Comp Sci Elect & Space Engn, SE-93187 Skelleftea, Sweden |
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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