{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T12:05:09Z","timestamp":1790251509985,"version":"4.1.0"},"reference-count":36,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["RTG\u00a02624"],"award-info":[{"award-number":["RTG\u00a02624"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["427806116"],"award-info":[{"award-number":["427806116"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Biometrical J"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Evaluating the change in gene expression is a common goal in many research areas, such as in toxicological studies, which are particularly important in pre\u2010clinical research. In practice, the analysis is often based on multiple\n                    <jats:italic>t<\/jats:italic>\n                    \u2010tests evaluated at the observed time points of the experiment, which limits the accuracy of determining the precise time at which the gene changes in expression. If a parametric approach is chosen, the analysis is often restricted to identifying the onset of an effect, but not its length. In this paper, we propose a parametric method to identify the time frame during which the gene expression significantly changes. This is achieved by fitting a parametric model and constructing a confidence band for its first derivative. The confidence band is derived by a two\u2010step bootstrap approach. It is summarized in terms of a hypothesis test, such that rejecting the null hypothesis means detecting a significant change in gene expression. Furthermore, a method for calculating confidence intervals for time points of interest (e.g., the beginning of significant change) is developed. We demonstrate the validity of our approach through a simulation study and present a variety of different applications to mouse gene expression data from a study investigating the effect of a Western diet on the progression of non\u2010alcoholic fatty liver\u00a0disease.\n                  <\/jats:p>","DOI":"10.1002\/bimj.70181","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T11:09:01Z","timestamp":1790248141000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identification of Changes in Gene Expression"],"prefix":"10.1002","volume":"68","author":[{"given":"Lucia","family":"Ameis","sequence":"first","affiliation":[{"name":"Institute of Medical Statistics and Computational Biology (IMSB), Faculty of Medicine University of Cologne Cologne Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7861-3892","authenticated-orcid":false,"given":"Kathrin","family":"M\u00f6llenhoff","sequence":"additional","affiliation":[{"name":"Institute of Medical Statistics and Computational Biology (IMSB), Faculty of Medicine University of Cologne Cologne Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"Alexa A. andJ.Rahnenf\u00fchrer.2024. \u201ctopGO: Enrichment Analysis for Gene Ontology.\u201dR Package Version 2.56.0. 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