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Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges
Shandong University, Jinan.
Shandong University, Jinan.
Institute of Computing Technology, Chinese Academy of Sciences.
Huawei Singapore Research Centre.
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2017 (English)In: Computational and structural biotechnology journal, E-ISSN 2001-0370, Vol. 15, 403-411 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 15, 403-411 p.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-65570DOI: 10.1016/j.csbj.2017.07.004PubMedID: 28883909Scopus ID: 2-s2.0-85028747817OAI: oai:DiVA.org:ltu-65570DiVA: diva2:1140124
Note

Validerad;2017;Nivå 2;2017-09-11 (andbra)

Available from: 2017-09-11 Created: 2017-09-11 Last updated: 2017-11-24Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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