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2015-02-26Zeitschriftenartikel DOI: 10.1186/s12864-015-1315-9
IPred - integrating ab initio and evidence based gene predictions to improve prediction accuracy
dc.contributor.authorZickmann, Franziska
dc.contributor.authorRenard, Bernhard Y.
dc.date.accessioned2018-05-07T18:07:38Z
dc.date.available2018-05-07T18:07:38Z
dc.date.created2015-03-04
dc.date.issued2015-02-26none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/reMs4bRO6uB2/PDF/20ZSeojieVA32.pdf
dc.identifier.urihttp://edoc.rki.de/176904/2024
dc.description.abstractBackground: Gene prediction is a challenging but crucial part in most genome analysis pipelines. Various methods have evolved that predict genes ab initio on reference sequences or evidence based with the help of additional information, such as RNA-Seq reads or EST libraries. However, none of these strategies is bias-free and one method alone does not necessarily provide a complete set of accurate predictions. Results: We present IPred (Integrative gene Prediction), a method to integrate ab initio and evidence based gene identifications to complement the advantages of different prediction strategies. IPred builds on the output of gene finders and generates a new combined set of gene identifications, representing the integrated evidence of the single method predictions. Conclusion: We evaluate IPred in simulations and real data experiments on Escherichia Coli and human data. We show that IPred improves the prediction accuracy in comparison to single method predictions and to existing methods for prediction combination.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut
dc.subjectGene predictioneng
dc.subjectGene finder combinationeng
dc.subjectGenome annotationeng
dc.subjectRNA-Seq integrationeng
dc.subject.ddc610 Medizin
dc.titleIPred - integrating ab initio and evidence based gene predictions to improve prediction accuracy
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10038908
dc.identifier.doi10.1186/s12864-015-1315-9
dc.identifier.doihttp://dx.doi.org/10.25646/1949
local.edoc.container-titleBMC Genomics
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://www.biomedcentral.com/1471-2164/16/134
local.edoc.container-publisher-nameBioMedCentral
local.edoc.container-volume16
local.edoc.container-issue134
local.edoc.container-year2015

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