Bayesian modelling of time series data (BayModTS) : a FAIR workflow to process sparse and highly variable data

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dc.contributor.authorHöpfl, Sebastian
dc.contributor.authorAlbadry, Mohamed
dc.contributor.authorDahmen, Uta
dc.contributor.authorHerrmann, Karl-Heinz
dc.contributor.authorKindler, Eva
dc.contributor.authorKönig, Matthias
dc.contributor.authorReichenbach, Jürgen R.
dc.contributor.authorTautenhahn, Hans-Michael
dc.contributor.authorWei, Weiwei
dc.contributor.authorZhao, Wan-Ting
dc.contributor.authorRadde, Nicole
dc.date.accessioned2025-09-16T15:37:34Z
dc.date.issued2024
dc.identifier.issn1367-4811
dc.identifier.other1936247011
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-170920de
dc.identifier.urihttps://elib.uni-stuttgart.de/handle/11682/17092
dc.identifier.urihttps://doi.org/10.18419/opus-17073
dc.language.isoen
dc.relation.uridoi:10.1093/bioinformatics/btae312
dc.rightsCC-BY
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc510
dc.subject.ddc570
dc.subject.ddc610
dc.titleBayesian modelling of time series data (BayModTS) : a FAIR workflow to process sparse and highly variable dataen
dc.typearticle
dc.type.versionpublishedVersion
ubs.fakultaetMathematik und Physik
ubs.fakultaetFakultätsübergreifend / Sonstige Einrichtung
ubs.institutInstitut für Stochastik und Anwendungen
ubs.institutFakultätsübergreifend / Sonstige Einrichtung
ubs.publikation.seiten8
ubs.publikation.sourceBioinformatics 40 (2024), issue 5, No. btae312
ubs.publikation.typZeitschriftenartikel
ubs.unilizenzOK

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