ISMARA : automated modeling of genomic signals as a democracy of regulatory motifs

Balwierz, Piotr J.; Pachkov, Mikhail; Arnold, Phil; Gruber, Andreas J.; Zavolan, Mihaela; van Nimwegen, Erik

ISMARA : automated modeling of genomic signals as a democracy of regulatory motifs

Dateien

Balwierz_2-1211bs4q2j2qe8.pdfGröße: 1.45 MBDownloads: 270

Datum

2014

Autor:innen

Balwierz, Piotr J.

Pachkov, Mikhail

Arnold, Phil

Gruber, Andreas J.

Zavolan, Mihaela

van Nimwegen, Erik

Open Access-Veröffentlichung

Open Access Hybrid

Sammlungen

Biologie

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Genome research. Cold Spring Harbor Laboratory Press. 2014, 24(5), pp. 869-884. ISSN 1054-9803. eISSN 1549-5469. Available under: doi: 10.1101/gr.169508.113

Zusammenfassung

Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited. Given that there are thousands of potential regulators in mammals, it is not practical to use direct experimentation to identify which of these play a key role for a particular system of interest. We developed a methodology that models gene expression or chromatin modifications in terms of genome-wide predictions of regulatory sites and completely automated it into a web-based tool called ISMARA (Integrated System for Motif Activity Response Analysis). Given only gene expression or chromatin state data across a set of samples as input, ISMARA identifies the key TFs and miRNAs driving expression/chromatin changes and makes detailed predictions regarding their regulatory roles. These include predicted activities of the regulators across the samples, their genome-wide targets, enriched gene categories among the targets, and direct interactions between the regulators. Applying ISMARA to data sets from well-studied systems, we show that it consistently identifies known key regulators ab initio. We also present a number of novel predictions including regulatory interactions in innate immunity, a master regulator of mucociliary differentiation, TFs consistently disregulated in cancer, and TFs that mediate specific chromatin modifications.

Fachgebiet (DDC)

570 Biowissenschaften, Biologie

Zitieren

ISO 690

BALWIERZ, Piotr J., Mikhail PACHKOV, Phil ARNOLD, Andreas J. GRUBER, Mihaela ZAVOLAN, Erik VAN NIMWEGEN, 2014. ISMARA : automated modeling of genomic signals as a democracy of regulatory motifs. In: Genome research. Cold Spring Harbor Laboratory Press. 2014, 24(5), pp. 869-884. ISSN 1054-9803. eISSN 1549-5469. Available under: doi: 10.1101/gr.169508.113

BibTex

@article{Balwierz2014-05ISMAR-51013,
  year={2014},
  doi={10.1101/gr.169508.113},
  title={ISMARA : automated modeling of genomic signals as a democracy of regulatory motifs},
  number={5},
  volume={24},
  issn={1054-9803},
  journal={Genome research},
  pages={869--884},
  author={Balwierz, Piotr J. and Pachkov, Mikhail and Arnold, Phil and Gruber, Andreas J. and Zavolan, Mihaela and van Nimwegen, Erik}
}

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Begutachtet

Ja