Show simple item record

dc.contributor.authorSztromwasser, Pawełeng
dc.contributor.authorPuntervoll, Påleng
dc.contributor.authorPetersen, Kjelleng
dc.date.accessioned2014-04-11T13:49:30Z
dc.date.available2014-04-11T13:49:30Z
dc.date.issued2011eng
dc.identifier.issn1613-4516en_US
dc.identifier.otherhttp://journal.imbio.de/articles/pdf/jib-163.pdfeng
dc.identifier.urihttps://hdl.handle.net/1956/7904
dc.description.abstractBiological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a com- mon practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinfor- matics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.en_US
dc.language.isoengeng
dc.publisherIMBio e.V.en_US
dc.relation.ispartof<a href="http://hdl.handle.net/1956/7906" target="blank">Throughput and robustness of bioinformatics pipelines for genome-scale data analysis</a>en_US
dc.rightsAttribution-NonCommercial-NoDerivs CC BY-NC-NDeng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0eng
dc.titleData partitioning enables the use of standard SOAP Web Services in genome-scale workflowsen_US
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2011 The Authorsen_US
dc.source.articlenumber163
dc.identifier.doihttps://doi.org/10.2390/biecoll-jib-2011-163
dc.identifier.cristin834107
dc.source.journalJournal of Integrated Bioinformatics
dc.source.408
dc.source.142


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs CC BY-NC-ND
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs CC BY-NC-ND