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Boosting analyses in the life sciences via clusters, grids and clouds

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URI: https://hdl.handle.net/10016/33739
ISSN: 0167-739X
DOI: https://doi.org/10.1016/j.future.2016.11.001
UXXI: AR/0000018585
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boosting_FGCS_2017_pp.pdf (425.11 KB)
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2017-02-01
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Elsevier
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Abstract
In the last 20 years, computational methods have become an important part of developing emerging technologies for the field of bioinformatics and biomedicine. Those methods rely heavily on large scale computational resources as they need to manage Tbytes or Pbytes of data with large-scale structural and functional relationships, TFlops or PFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analyzing data. This special issue contains papers showing existing solutions and latest developments in Life Sciences and Computing Sciences to collaboratively explore new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making. (C) 2016 Published by Elsevier B.V.
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bioinformatics, biomedicine, and health, genomics, life sciences, cloud computing, workflows, framework
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Gesing, S., Carretero, J., García Blás, J., Montagnat, J. (2017). Boosting analyses in the life sciences via clusters, grids and clouds. Future Generation Computer Systems, 67, pp. 325-328. https://doi.org/10.1016/j.future.2016.11.001
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