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dc.date.accessioned2015-04-13T18:24:52Z
dc.date.available2015-04-13T18:24:52Z
dc.date.created2015-01-22T09:01:23Z
dc.date.issued2014
dc.identifier.citationNeumann, Ralf Stefan Kumar, Surendra Haverkamp, Thomas Hendricus Augustus Shalchian-Tabrizi, Kamran . BLASTGrabber: A bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data. BMC Bioinformatics. 2014, 15(128)
dc.identifier.urihttp://hdl.handle.net/10852/43552
dc.description.abstractBackground Advances in sequencing efficiency have vastly increased the sizes of biological sequence databases, including many thousands of genome-sequenced species. The BLAST algorithm remains the main search engine for retrieving sequence information, and must consequently handle data on an unprecedented scale. This has been possible due to high-performance computers and parallel processing. However, the raw BLAST output from contemporary searches involving thousands of queries becomes ill-suited for direct human processing. Few programs attempt to directly visualize and interpret BLAST output; those that do often provide a mere basic structuring of BLAST data. Results Here we present a bioinformatics application named BLASTGrabber suitable for high-throughput sequencing analysis. BLASTGrabber, being implemented as a Java application, is OS-independent and includes a user friendly graphical user interface. Text or XML-formatted BLAST output files can be directly imported, displayed and categorized based on BLAST statistics. Query names and FASTA headers can be analysed by text-mining. In addition to visualizing sequence alignments, BLAST data can be ordered as an interactive taxonomy tree. All modes of analysis support selection, export and storage of data. A Java interface-based plugin structure facilitates the addition of customized third party functionality. Conclusion The BLASTGrabber application introduces new ways of visualizing and analysing massive BLAST output data by integrating taxonomy identification, text mining capabilities and generic multi-dimensional rendering of BLAST hits. The program aims at a non-expert audience in terms of computer skills; the combination of new functionalities makes the program flexible and useful for a broad range of operations.en_US
dc.languageEN
dc.language.isoenen_US
dc.publisherBioMed Central
dc.rightsAttribution 2.0 Generic
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/
dc.titleBLASTGrabber: A bioinformatic tool for visualization, analysis and sequence selection of massive BLAST dataen_US
dc.typeJournal articleen_US
dc.creator.authorNeumann, Ralf Stefan
dc.creator.authorKumar, Surendra
dc.creator.authorHaverkamp, Thomas Hendricus Augustus
dc.creator.authorShalchian-Tabrizi, Kamran
cristin.unitcode185,15,29,0
cristin.unitnameInstitutt for biovitenskap
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1204564
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=BMC Bioinformatics&rft.volume=15&rft.spage=&rft.date=2014
dc.identifier.jtitleBMC Bioinformatics
dc.identifier.volume15
dc.identifier.pagecount11
dc.identifier.doihttp://dx.doi.org/10.1186/1471-2105-15-128
dc.identifier.urnURN:NBN:no-47922
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn1471-2105
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/43552/1/1471-2105-15-128shalchian-tabrizi.pdf
dc.type.versionPublishedVersion
cristin.articleid128


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