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Securing the future of research computing in the biosciences

Leng, J.; Shoura, M.; McLeish, T.C.B.; Real, A.N.; Hardey, M.; McCafferty, J.; Ranson, N.A.; Harris, S.A.

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Authors

J. Leng

M. Shoura

T.C.B. McLeish

Dr Alan Real alan.n.real@durham.ac.uk
Director Of Advanced Research Computing

J. McCafferty

N.A. Ranson

S.A. Harris



Abstract

Improvements in technology often drive scientific discovery. Therefore, research requires sustained investment in the latest equipment and training for the researchers who are going to use it. Prioritising and administering infrastructure investment is challenging because future needs are difficult to predict. In the past, highly computationally demanding research was associated primarily with particle physics and astronomy experiments. However, as biology becomes more quantitative and bioscientists generate more and more data, their computational requirements may ultimately exceed those of physical scientists. Computation has always been central to bioinformatics, but now imaging experiments have rapidly growing data processing and storage requirements. There is also an urgent need for new modelling and simulation tools to provide insight and understanding of these biophysical experiments. Bioscience communities must work together to provide the software and skills training needed in their areas. Research-active institutions need to recognise that computation is now vital in many more areas of discovery and create an environment where it can be embraced. The public must also become aware of both the power and limitations of computing, particularly with respect to their health and personal data.

Citation

Leng, J., Shoura, M., McLeish, T., Real, A., Hardey, M., McCafferty, J., …Harris, S. (2019). Securing the future of research computing in the biosciences. PLoS Computational Biology, 15(5), Article e1006958. https://doi.org/10.1371/journal.pcbi.1006958

Journal Article Type Article
Acceptance Date Apr 9, 2019
Publication Date May 16, 2019
Deposit Date Apr 29, 2019
Publicly Available Date Apr 30, 2019
Journal PLoS Computational Biology
Print ISSN 1553-734X
Electronic ISSN 1553-7358
Publisher Public Library of Science
Peer Reviewed Peer Reviewed
Volume 15
Issue 5
Article Number e1006958
DOI https://doi.org/10.1371/journal.pcbi.1006958
Public URL https://durham-repository.worktribe.com/output/1297760

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Accepted Journal Article (197 Kb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
Copyright: © 2019 Leng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.







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