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Eduati, F.* ; di Camillo, B.* ; Karbiener, M.* ; Scheideler, M.* ; Corà, D.* ; Caselle, M.* ; Toffolo, G.*

Dynamic modeling of miRNA-mediated feed-forward loops.

J. Comput. Biol. 19, 188-199 (2012)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Given the important role of microRNAs (miRNAs) in genome-wide regulation of gene expression, increasing interest is devoted to mixed transcriptional and post-transcriptional regulatory networks analyzing the combinatorial effect of transcription factors (TFs) and miRNAs on target genes. In particular, miRNAs are known to be involved in feed-forward loops (FFLs), where a TF regulates a miRNA and they both regulate a target gene. Different algorithms have been proposed to identify miRNA targets, based on pairing between the 5' region of the miRNA and the 3'UTR of the target gene, and correlation between miRNA host genes and target mRNA expression data. Here we propose a quantitative approach integrating an existing method for mixed FFL identification based on sequence analysis with differential equation modeling approach that permits us to select active FFLs based on their dynamics. Different models are assessed based on their ability to properly reproduce miRNA and mRNA expression data in terms of identification criteria, namely: goodness of fit, precision of the estimates, and comparison with submodels. In comparison with standard approaches based on correlation, our method improves in specificity. As a case study, we applied our method to adipogenic differentiation gene expression data providing potential novel players in this regulatory network. Supplementary Material for this article is available at www.liebertonline.com/cmb.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache englisch
Veröffentlichungsjahr 2012
HGF-Berichtsjahr 0
ISSN (print) / ISBN 1066-5277
e-ISSN 1557-8666
Quellenangaben Band: 19, Heft: 2, Seiten: 188-199 Artikelnummer: , Supplement: ,
Verlag Mary Ann Liebert
Begutachtungsstatus Peer reviewed
PubMed ID 22300320
Erfassungsdatum 2012-12-31