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@ARTICLE{Kappenberg:167284,
      author       = {F. Kappenberg and M. Grinberg and X. Jiang and A.
                      Kopp-Schneider$^*$ and J. G. Hengstler and J. Rahnenführer},
      title        = {{C}omparison {O}f {O}bservation-{B}ased {A}nd
                      {M}odel-{B}ased {I}dentification {O}f {A}lert
                      {C}oncentrations {F}rom {C}oncentration-{E}xpression
                      {D}ata.},
      journal      = {Bioinformatics},
      volume       = {37},
      number       = {14},
      issn         = {1460-2059},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2021-00239},
      pages        = {1990-1996},
      year         = {2021},
      note         = {2021 Jan 30;37(14):1990-1996},
      abstract     = {An important goal of concentration-response studies in
                      toxicology is to determine an 'alert' concentration where a
                      critical level of the response variable is exceeded. In a
                      classical observation-based approach, only measured
                      concentrations are considered as potential alert
                      concentrations. Alternatively, a parametric curve is fitted
                      to the data that describes the relationship between
                      concentration and response. For a prespecified effect level,
                      both an absolute estimate of the alert concentration and an
                      estimate of the lowest concentration where the effect level
                      is exceeded significantly are of interest.In a simulation
                      study for gene expression data, we compared the
                      observation-based and the model-based approach for both
                      absolute and significant exceedance of the prespecified
                      effect level. Results show that, compared to the
                      observation-based approach, the model-based approach
                      overestimates the true alert concentration less often and
                      more frequently leads to a valid estimate, especially for
                      genes with large variance.The code used for the simulation
                      studies is available via the GitHub repository:
                      https://github.com/FKappenberg/Paper-IdentificationAlertConcentrations.Supplementary
                      data are available at Bioinformatics online.},
      cin          = {C060},
      ddc          = {570},
      cid          = {I:(DE-He78)C060-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33515236},
      doi          = {10.1093/bioinformatics/btab043},
      url          = {https://inrepo02.dkfz.de/record/167284},
}