Community-driven computational biology with Debian Linux

Background The Open Source movement and its technologies are popular in the bioinformatics community because they provide freely available tools and resources for research. In order to feed the steady demand for updates on software and associated data, a service infrastructure is required for sharin...

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Veröffentlicht in:BMC bioinformatics Jg. 11; H. Suppl 12; S. S5
Hauptverfasser: Möller, Steffen, Krabbenhöft, Hajo Nils, Tille, Andreas, Paleino, David, Williams, Alan, Wolstencroft, Katy, Goble, Carole, Holland, Richard, Belhachemi, Dominique, Plessy, Charles
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 21.12.2010
Springer Nature B.V
Schlagworte:
Algorithms
Bioinformatics
Biomedical and Life Sciences
Computational Biology - methods
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Infrastructure
Internet
Life Sciences
Microarrays
Proceedings
Software
Command Line
Remote Machine
Cloud Computing
Heterogeneous Computing Environment
Open Source Movement
ISSN:1471-2105, 1471-2105
Online-Zugang:Volltext
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Zusammenfassung:Background The Open Source movement and its technologies are popular in the bioinformatics community because they provide freely available tools and resources for research. In order to feed the steady demand for updates on software and associated data, a service infrastructure is required for sharing and providing these tools to heterogeneous computing environments. Results The Debian Med initiative provides ready and coherent software packages for medical informatics and bioinformatics. These packages can be used together in Taverna workflows via the UseCase plugin to manage execution on local or remote machines. If such packages are available in cloud computing environments, the underlying hardware and the analysis pipelines can be shared along with the software. Conclusions Debian Med closes the gap between developers and users. It provides a simple method for offering new releases of software and data resources, thus provisioning a local infrastructure for computational biology. For geographically distributed teams it can ensure they are working on the same versions of tools, in the same conditions. This contributes to the world-wide networking of researchers.
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ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-11-S12-S5