{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:17:54Z","timestamp":1761844674145,"version":"3.37.3"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2016,12,2]],"date-time":"2016-12-02T00:00:00Z","timestamp":1480636800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institute of Health","doi-asserted-by":"publisher","award":["SFB704"],"award-info":[{"award-number":["SFB704"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. ImpulseDE is an R package suited to capture these patterns in high throughput time series datasets. By fitting a representative impulse model to each gene, it reports differentially expressed genes across time points from a single or between two time courses from two experiments. To optimize running time, the code uses clustering and multi-threading. By applying ImpulseDE, we demonstrate its power to represent underlying biology of gene expression in microarray and RNA-Seq data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and Implementation<\/jats:title><jats:p>ImpulseDE is available on Bioconductor (https:\/\/bioconductor.org\/packages\/ImpulseDE\/).<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btw665","type":"journal-article","created":{"date-parts":[[2016,10,18]],"date-time":"2016-10-18T20:17:23Z","timestamp":1476821843000},"page":"757-759","source":"Crossref","is-referenced-by-count":37,"title":["ImpulseDE: detection of differentially expressed genes in time series data using impulse models"],"prefix":"10.1093","volume":"33","author":[{"given":"Jil","family":"Sander","sequence":"first","affiliation":[{"name":"Genomics and Immunoregulation, LIMES-Institute, University of Bonn, Bonn, Germany"}]},{"given":"Joachim L","family":"Schultze","sequence":"additional","affiliation":[{"name":"Genomics and Immunoregulation, LIMES-Institute, University of Bonn, Bonn, Germany"},{"name":"Single Cell Genomics and Epigenomics Unit at the University of Bonn and the German Center for Neurodegenerative Diseases, Bonn, Germany"}]},{"given":"Nir","family":"Yosef","sequence":"additional","affiliation":[{"name":"Electrical Engineering and Computer Science, Center for Computational Biology, University of California Berkeley, Berkeley, CA, USA"}]}],"member":"286","published-online":{"date-parts":[[2016,12,2]]},"reference":[{"key":"2023020204504035500_btw665-B1","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1093\/bioinformatics\/btu274","article-title":"Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation","volume":"30","author":"\u00c4ji\u00f6","year":"2014","journal-title":"Bioinformatics"},{"key":"2023020204504035500_btw665-B3","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1038\/nrg3244","article-title":"Studying and modelling dynamic biological processes using time-series gene expression data","volume":"13","author":"Bar-Joseph","year":"2012","journal-title":"Nat. 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