From the desktop to the grid: scalable bioinformatics via workflow conversion. Issue 1 (December 2016)
- Record Type:
- Journal Article
- Title:
- From the desktop to the grid: scalable bioinformatics via workflow conversion. Issue 1 (December 2016)
- Main Title:
- From the desktop to the grid: scalable bioinformatics via workflow conversion
- Authors:
- de la Garza, Luis
Veit, Johannes
Szolek, Andras
Röttig, Marc
Aiche, Stephan
Gesing, Sandra
Reinert, Knut
Kohlbacher, Oliver - Abstract:
- Abstract Background Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks. There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free —an aspect that could potentially drive away members of the scientific community. Results We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-calledCommon Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: theKonstanz Information Miner, an engine which we see as aAbstract Background Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks. There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free —an aspect that could potentially drive away members of the scientific community. Results We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-calledCommon Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: theKonstanz Information Miner, an engine which we see as a formidable workflow editor, and theGrid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources. Conclusions Our work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results. … (more)
- Is Part Of:
- BMC bioinformatics. Volume 17:Issue 1(2016)
- Journal:
- BMC bioinformatics
- Issue:
- Volume 17:Issue 1(2016)
- Issue Display:
- Volume 17, Issue 1 (2016)
- Year:
- 2016
- Volume:
- 17
- Issue:
- 1
- Issue Sort Value:
- 2016-0017-0001-0000
- Page Start:
- 1
- Page End:
- 12
- Publication Date:
- 2016-12
- Subjects:
- Workflow -- Interoperability -- KNIME -- Grid -- Cloud -- Galaxy -- gUSE
Bioinformatics -- Periodicals
Computational biology -- Periodicals
570.285 - Journal URLs:
- http://www.biomedcentral.com/bmcbioinformatics/ ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=13 ↗
http://link.springer.com/ ↗ - DOI:
- 10.1186/s12859-016-0978-9 ↗
- Languages:
- English
- ISSNs:
- 1471-2105
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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British Library HMNTS - ELD Digital store - Ingest File:
- 9951.xml