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Results: 65
Number of items: 65
  • Naue, J., Sänger, T., Hoefsloot, H. C. J., Lutz-Bonengel, S., Kloosterman, A. D., & Verschure, P. J. (2018). Proof of concept study of age-dependent DNA methylation markers across different tissues by massive parallel sequencing. Forensic Science International. Genetics, 36, 152-159. https://doi.org/10.1016/j.fsigen.2018.07.007
  • Naue, J., Hoefsloot, H. C. J., Kloosterman, A. D., & Verschure, P. J. (2018). Forensic DNA methylation profiling from minimal traces: How low can we go? Forensic Science International. Genetics, 33, 17-23. https://doi.org/10.1016/j.fsigen.2017.11.004
  • Open Access
    Beckman, W., Vuist, I. M., Kempe, H., & Verschure, P. J. (2018). Cell-to-Cell Transcription Variability as Measured by Single-Molecule RNA FISH to Detect Epigenetic State Switching. In A. Jeltsch, & M. G. Rots (Eds.), Epigenome Editing: Methods and Protocols (pp. 385-393). (Methods in Molecular Biology). Humana Press. https://doi.org/10.1007/978-1-4939-7774-1_21
  • Goubert, D., Beckman, W. F., Verschure, P. J., & Rots, M. G. (2017). Epigenetic editing: towards realization of the curable genome concept. Convergent Science Physical Oncology, 3(1), Article 013006. https://doi.org/10.1088/2057-1739/aa5cc0
  • Magnani, L., Frigè, G., Gadaleta, R. M., Corleone, G., Fabris, S., Kempe, H., Verschure, P. J., Barozzi, I., Vircillo, V., Hong, S. P., Perone, Y., Saini, M., Trumpp, A., Viale, G., Neri, A., Ali, S., Colleoni, M. A., Pruneri, G., & Minucci, S. (2017). Acquired CYP19A1 amplification is an early specific mechanism of aromatase inhibitor resistance in ERα metastatic breast cancer. Nature genetics, 49(3), 444-450. https://doi.org/10.1038/ng.3773
  • van Hagen, M., Piebes, D., de Leeuw, W. C., Vuist, I., van Roon-Mom, W. M., Moerland, P. D., & Verschure, P. J. (2017). Additional file 2: of The dynamics of early-state transcriptional changes and aggregate formation in a Huntington's disease cell model [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.c.3778547_d2.v1
  • van Hagen, M., Piebes, D., de Leeuw, W. C., Vuist, I., van Roon-Mom, W. M., Moerland, P., & Verschure, P. J. (2017). Additional file 4: of The dynamics of early-state transcriptional changes and aggregate formation in a Huntington’s disease cell model [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.c.3778547_d4.v1
  • van Hagen, M., Piebes, D., de Leeuw, W. C., Vuist, I., van Roon-Mom, W. M., Moerland, P. D., & Verschure, P. J. (2017). Additional file 5: of The dynamics of early-state transcriptional changes and aggregate formation in a Huntington’s disease cell model [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.c.3778547_d5.v1
  • van Hagen, M., Piebes, D., de Leeuw, W. C., Vuist, I., van Roon-Mom, W. M., Moerland, P. D., & Verschure, P. J. (2017). Additional file 6: of The dynamics of early-state transcriptional changes and aggregate formation in a Huntington’s disease cell model [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.c.3778547_d6.v1
  • Open Access
    Naue, J., Hoefsloot, H. C. J., Mook, O. R. F., Rijlaarsdam-Hoekstra, L., van der Zwalm, M. C. H., Henneman, P., Kloosterman, A. D., & Verschure, P. J. (2017). Chronological age prediction based on DNA methylation: Massive parallel sequencing and random forest regression. Forensic Science International. Genetics, 31, 19-28. https://doi.org/10.1016/j.fsigen.2017.07.015
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