A Galaxy workflow for the functional annotation of metagenomic samples

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dc.contributor.author Pilalis, E en
dc.contributor.author Ladoukakis, E en
dc.contributor.author Kolisis, FN en
dc.contributor.author Chatziioannou, A en
dc.date.accessioned 2014-03-01T02:53:32Z
dc.date.available 2014-03-01T02:53:32Z
dc.date.issued 2012 en
dc.identifier.issn 03029743 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/36394
dc.subject Galaxy en
dc.subject Gene Ontology Terms en
dc.subject Metagenomics en
dc.subject Protein Function Prediction en
dc.subject.other Bioinformatics tools en
dc.subject.other Functional annotation en
dc.subject.other Gene ontology en
dc.subject.other Intuitive interfaces en
dc.subject.other Large datasets en
dc.subject.other Metagenomics en
dc.subject.other MySQL database en
dc.subject.other Perl scripts en
dc.subject.other Protein function prediction en
dc.subject.other Work-flows en
dc.subject.other Artificial intelligence en
dc.subject.other Bioinformatics en
dc.subject.other Galaxies en
dc.title A Galaxy workflow for the functional annotation of metagenomic samples en
heal.type conferenceItem en
heal.identifier.primary 10.1007/978-3-642-30448-4_31 en
heal.identifier.secondary http://dx.doi.org/10.1007/978-3-642-30448-4_31 en
heal.publicationDate 2012 en
heal.abstract In this work, an annotation workflow was developed, which performs a series of annotation tasks to sequences originating from metagenomic samples, using standard bioinformatics tools and Perl scripts. The Perl scripts interact with a Mysql database in order to store all annotation results to the respective tables, thus rendering easy the quick access and querying to all data. The whole pipeline was integrated into a Galaxy server, which provides a simple and intuitive interface that allows the user to easily create, run and share workflows for large datasets. © 2012 Springer-Verlag. en
heal.journalName Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) en
dc.identifier.doi 10.1007/978-3-642-30448-4_31 en
dc.identifier.volume 7297 LNCS en
dc.identifier.spage 247 en
dc.identifier.epage 253 en

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