New Results
Self-learning algorithm for denoising and advancing the integration of scRNA-seq datasets improves the identification of resilient and susceptible retinal ganglion cell types
Bruce A. Rheaume, View ORCID ProfileEphraim F. Trakhtenberg
doi: https://doi.org/10.1101/2021.10.15.464552
Bruce A. Rheaume
1Department of Neuroscience, University of Connecticut School of Medicine, 263 Farmington Ave., Farmington, CT, 06030, USA
Ephraim F. Trakhtenberg
1Department of Neuroscience, University of Connecticut School of Medicine, 263 Farmington Ave., Farmington, CT, 06030, USA
Article usage
Posted March 10, 2022.
Self-learning algorithm for denoising and advancing the integration of scRNA-seq datasets improves the identification of resilient and susceptible retinal ganglion cell types
Bruce A. Rheaume, Ephraim F. Trakhtenberg
bioRxiv 2021.10.15.464552; doi: https://doi.org/10.1101/2021.10.15.464552
Subject Area
Subject Areas
- Biochemistry (11752)
- Bioengineering (8752)
- Bioinformatics (29200)
- Biophysics (14974)
- Cancer Biology (12096)
- Cell Biology (17411)
- Clinical Trials (138)
- Developmental Biology (9421)
- Ecology (14182)
- Epidemiology (2067)
- Evolutionary Biology (18308)
- Genetics (12245)
- Genomics (16803)
- Immunology (11869)
- Microbiology (28097)
- Molecular Biology (11594)
- Neuroscience (60969)
- Paleontology (451)
- Pathology (1871)
- Pharmacology and Toxicology (3238)
- Physiology (4959)
- Plant Biology (10427)
- Synthetic Biology (2886)
- Systems Biology (7340)
- Zoology (1651)