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  Evaluation of methods for modeling transcription factor sequence specificity

Weirauch, M. T., Cote, A., Norel, R., Annala, M., Zhao, Y., Riley, T. R., et al. (2013). Evaluation of methods for modeling transcription factor sequence specificity. Nature biotechnology, 31(2), 126-34. doi:10.1038/nbt.2486.

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© 2013 Nature Publishing Group
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Weirauch, M. T., Autor
Cote, A., Autor
Norel, R., Autor
Annala, M., Autor
Zhao, Y., Autor
Riley, T. R., Autor
Saez-Rodriguez, J., Autor
Cokelaer, T., Autor
Vedenko, A., Autor
Talukder, S., Autor
Consortium, Dream, Autor
Agius, P., Autor
Arvey, A., Autor
Bucher, P., Autor
Callan, C. G., Jr., Autor
Chang, C. W., Autor
Chen, C. Y., Autor
Chen, Y. S., Autor
Chu, Y. W., Autor
Grau, J., Autor
Grosse, I., AutorJagannathan, V., AutorKeilwagen, J., AutorKielbasa, S. M.1, Autor           Kinney, J. B., AutorKlein, H., AutorKursa, M. B., AutorLahdesmaki, H., AutorLaurila, K., AutorLei, C., AutorLeslie, C., AutorLinhart, C., AutorMurugan, A., AutorMysickova, A., AutorNoble, W. S., AutorNykter, M., AutorOrenstein, Y., AutorPosch, S., AutorRuan, J., AutorRudnicki, W. R., AutorSchmid, C. D., AutorShamir, R., AutorSung, W. K., AutorVingron, M.2, Autor           Zhang, Z., AutorBussemaker, H. J., AutorMorris, Q. D., AutorBulyk, M. L., AutorStolovitzky, G., AutorHughes, T. R., Autor mehr..
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
2Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, Berlin, Germany, ou_1479639              

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 Zusammenfassung: Genomic analyses often involve scanning for potential transcription factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a protein's DNA-binding specificity, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For nine TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro-derived motifs performed similarly to motifs derived from the in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices trained by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10% of the TFs examined here). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.

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Sprache(n): eng - English
 Datum: 2013-02
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1038/nbt.2486
ISSN: 1546-1696 (Electronic)1087-0156 (Print)
 Art des Abschluß: -

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Titel: Nature biotechnology
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: New York : Gale Group Inc.
Seiten: - Band / Heft: 31 (2) Artikelnummer: - Start- / Endseite: 126 - 34 Identifikator: ISSN: 1087-0156
CoNE: https://pure.mpg.de/cone/journals/resource/954926980065