Bringing numerous methods for expression and promoter analysis to a public cloud computing service
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...
| Main Authors: | , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Oxford University Press
2017
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| _version_ | 1826307085850116096 |
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| author | Polański, K Gao, B Mason, SA Brown, P Ott, S Denby, KJ Wild, DL |
| author_facet | Polański, K Gao, B Mason, SA Brown, P Ott, S Denby, KJ Wild, DL |
| author_sort | Polański, K |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T06:57:41Z |
| format | Journal article |
| id | oxford-uuid:feb1a555-a266-4e6b-ac7a-c170759af6f8 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:57:41Z |
| publishDate | 2017 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | oxford-uuid:feb1a555-a266-4e6b-ac7a-c170759af6f82022-03-27T13:38:37ZBringing numerous methods for expression and promoter analysis to a public cloud computing serviceJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:feb1a555-a266-4e6b-ac7a-c170759af6f8EnglishSymplectic ElementsOxford University Press2017Polański, KGao, BMason, SABrown, POtt, SDenby, KJWild, DLEvery 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. |
| spellingShingle | Polański, K Gao, B Mason, SA Brown, P Ott, S Denby, KJ Wild, DL Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
| title | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
| title_full | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
| title_fullStr | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
| title_full_unstemmed | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
| title_short | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
| title_sort | bringing numerous methods for expression and promoter analysis to a public cloud computing service |
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