New Results
Accurate prediction of single-cell DNA methylation states using deep learning
View ORCID ProfileChristof Angermueller, View ORCID ProfileHeather J. Lee, View ORCID ProfileWolf Reik, View ORCID ProfileOliver Stegle
doi: https://doi.org/10.1101/055715
Christof Angermueller
1European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
Heather J. Lee
2Epigenetics Programme, Babraham Institute, Cambridge, UK
3Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
Wolf Reik
2Epigenetics Programme, Babraham Institute, Cambridge, UK
3Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
Oliver Stegle
1European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
Article usage
Posted May 27, 2016.
Accurate prediction of single-cell DNA methylation states using deep learning
Christof Angermueller, Heather J. Lee, Wolf Reik, Oliver Stegle
bioRxiv 055715; doi: https://doi.org/10.1101/055715
Subject Area
Subject Areas
- Biochemistry (11739)
- Bioengineering (8750)
- Bioinformatics (29189)
- Biophysics (14967)
- Cancer Biology (12093)
- Cell Biology (17409)
- Clinical Trials (138)
- Developmental Biology (9419)
- Ecology (14178)
- Epidemiology (2067)
- Evolutionary Biology (18301)
- Genetics (12238)
- Genomics (16797)
- Immunology (11865)
- Microbiology (28068)
- Molecular Biology (11583)
- Neuroscience (60953)
- Paleontology (451)
- Pathology (1870)
- Pharmacology and Toxicology (3238)
- Physiology (4957)
- Plant Biology (10425)
- Synthetic Biology (2884)
- Systems Biology (7338)
- Zoology (1651)