Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning. [electronic resource]
Producer: 20190529Description: 311-314 p. digitalISSN:- 1548-7105
- Algorithms
- Animals
- Brain Mapping
- Cluster Analysis
- Computational Biology -- methods
- Computer Simulation
- Databases, Genetic
- Deep Learning
- Gene Expression Profiling
- Inflammation
- Intestines -- cytology
- Leukocytes, Mononuclear -- cytology
- Mice
- Phenotype
- Principal Component Analysis
- RNA -- analysis
- Reproducibility of Results
- Retina -- metabolism
- Sequence Analysis, RNA
- Single-Cell Analysis
- Software
- Transcriptome
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Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
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