{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:10:31Z","timestamp":1761743431015},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Targeted interventions in combination with the measurement of secondary effects can be used to computationally reverse engineer features of upstream non-transcriptional signaling cascades. Nested effect models (NEMs) have been introduced as a statistical approach to estimate the upstream signal flow from downstream nested subset structure of perturbation effects. The method was substantially extended later on by several authors and successfully applied to various datasets. The connection of NEMs to Bayesian Networks and factor graph models has been highlighted.<\/jats:p>\n               <jats:p>Results: Here, we introduce a computationally attractive extension of NEMs that enables the analysis of perturbation time series data, hence allowing to discriminate between direct and indirect signaling and to resolve feedback loops.<\/jats:p>\n               <jats:p>Availability: The implementation (R and C) is part of the Supplement to this article.<\/jats:p>\n               <jats:p>Contact: \u00a0frohlich@bit.uni-bonn.de<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq631","type":"journal-article","created":{"date-parts":[[2010,11,11]],"date-time":"2010-11-11T01:18:02Z","timestamp":1289438282000},"page":"238-244","source":"Crossref","is-referenced-by-count":26,"title":["Fast and efficient dynamic nested effects models"],"prefix":"10.1093","volume":"27","author":[{"given":"Holger","family":"Fr\u00f6hlich","sequence":"first","affiliation":[{"name":"1 Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Bonn-Aachen International Center for IT, Dahlmannstrasse 2, 53113 Bonn and 2Department of Chemistry and Biochemistry, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Gene Center Munich and Center for integrated Protein Science CiPSM, Feodor-Lynen-Strasse 25, 81377 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paurush","family":"Praveen","sequence":"additional","affiliation":[{"name":"1 Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Bonn-Aachen International Center for IT, Dahlmannstrasse 2, 53113 Bonn and 2Department of Chemistry and Biochemistry, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Gene Center Munich and Center for integrated Protein Science CiPSM, Feodor-Lynen-Strasse 25, 81377 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Achim","family":"Tresch","sequence":"additional","affiliation":[{"name":"1 Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Bonn-Aachen International Center for IT, Dahlmannstrasse 2, 53113 Bonn and 2Department of Chemistry and Biochemistry, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Gene Center Munich and Center for integrated Protein Science CiPSM, Feodor-Lynen-Strasse 25, 81377 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,11,10]]},"reference":[{"key":"2023012512171335200_B1","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1137\/0201008","article-title":"The transitive reduction of a directed graph","volume":"1","author":"Aho","year":"1972","journal-title":"SIAM J. 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