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A Python library for probabilistic analysis of single-cell omics data
DOI:10.1038/s41587-021-01206-w.png)
摘要
En
期刊
IF:
41.7
论文数:
1.2W
被引数:
10.1W
机构
引用论文
Joint probabilistic modeling of single-cell multi-omic data with totalVI单细胞多组数据的totalVI联合概率建模
NATURE METHODS
IF32.1
Enhancing scientific discoveries in molecular biology with deep generative models通过深度生成模型增强分子生物学的科学发现
Anisotropic behavior of exchange coupling in textured Nd2Fe14B/α-Fe multilayer films织构Nd2Fe14B/α-fe多层膜中交换耦合的各向异性行为
Mapping single-cell data to reference atlases by transfer learning通过迁移学习将单细胞数据映射到参考地图集
NATURE BIOTECHNOLOGY
IF41.7
Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep LearningSolo: 通过半监督深度学习在单细胞rna-seq中识别双峰
CELL SYSTEMS
IF7.7

