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Items: 7

1.

Genome-Scale Oscillations in DNA Methylation during Exit from Pluripotency.

Rulands S, Lee HJ, Clark SJ, Angermueller C, Smallwood SA, Krueger F, Mohammed H, Dean W, Nichols J, Rugg-Gunn P, Kelsey G, Stegle O, Simons BD, Reik W.

Cell Syst. 2018 Jul 25;7(1):63-76.e12. doi: 10.1016/j.cels.2018.06.012.

2.

Deep Learning for Predicting Refractive Error From Retinal Fundus Images.

Varadarajan AV, Poplin R, Blumer K, Angermueller C, Ledsam J, Chopra R, Keane PA, Corrado GS, Peng L, Webster DR.

Invest Ophthalmol Vis Sci. 2018 Jun 1;59(7):2861-2868. doi: 10.1167/iovs.18-23887.

PMID:
30025129
3.

Erratum to: DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning.

Angermueller C, Lee HJ, Reik W, Stegle O.

Genome Biol. 2017 May 12;18(1):90. doi: 10.1186/s13059-017-1233-z. No abstract available.

4.

DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning.

Angermueller C, Lee HJ, Reik W, Stegle O.

Genome Biol. 2017 Apr 11;18(1):67. doi: 10.1186/s13059-017-1189-z. Erratum in: Genome Biol. 2017 May 12;18(1):90.

5.

Deep learning for computational biology.

Angermueller C, Pärnamaa T, Parts L, Stegle O.

Mol Syst Biol. 2016 Jul 29;12(7):878. doi: 10.15252/msb.20156651. Review.

6.

Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity.

Angermueller C, Clark SJ, Lee HJ, Macaulay IC, Teng MJ, Hu TX, Krueger F, Smallwood S, Ponting CP, Voet T, Kelsey G, Stegle O, Reik W.

Nat Methods. 2016 Mar;13(3):229-232. doi: 10.1038/nmeth.3728. Epub 2016 Jan 11.

7.

Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity.

Smallwood SA, Lee HJ, Angermueller C, Krueger F, Saadeh H, Peat J, Andrews SR, Stegle O, Reik W, Kelsey G.

Nat Methods. 2014 Aug;11(8):817-820. doi: 10.1038/nmeth.3035. Epub 2014 Jul 20.

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