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Journal article

Bringing numerous methods for expression and promoter analysis to a public cloud computing service

Abstract:
Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/bioinformatics/btx692

Authors


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Role:
Author
ORCID:
0000-0002-2586-9576
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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
ORCID:
0000-0002-7405-7507


Publisher:
Oxford University Press
Journal:
Bioinformatics More from this journal
Volume:
34
Issue:
5
Pages:
884-886
Place of publication:
England
Publication date:
2017-11-06
Acceptance date:
2017-11-03
DOI:
EISSN:
1367-4811
ISSN:
1367-4803
Pmid:
29126246


Language:
English
Keywords:
Pubs id:
1101053
Local pid:
pubs:1101053
Deposit date:
2022-01-27

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