Unknown

Dataset Information

0

Surface protein imputation from single cell transcriptomes by deep neural networks.


ABSTRACT: While single cell RNA sequencing (scRNA-seq) is invaluable for studying cell populations, cell-surface proteins are often integral markers of cellular function and serve as primary targets for therapeutic intervention. Here we propose a transfer learning framework, single cell Transcriptome to Protein prediction with deep neural network (cTP-net), to impute surface protein abundances from scRNA-seq data by learning from existing single-cell multi-omic resources.

SUBMITTER: Zhou Z 

PROVIDER: S-EPMC6994606 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

altmetric image

Publications

Surface protein imputation from single cell transcriptomes by deep neural networks.

Zhou Zilu Z   Ye Chengzhong C   Wang Jingshu J   Zhang Nancy R NR  

Nature communications 20200131 1


While single cell RNA sequencing (scRNA-seq) is invaluable for studying cell populations, cell-surface proteins are often integral markers of cellular function and serve as primary targets for therapeutic intervention. Here we propose a transfer learning framework, single cell Transcriptome to Protein prediction with deep neural network (cTP-net), to impute surface protein abundances from scRNA-seq data by learning from existing single-cell multi-omic resources. ...[more]

Similar Datasets

| S-EPMC11020228 | biostudies-literature
| S-EPMC9979929 | biostudies-literature
| S-EPMC9940350 | biostudies-literature
| S-EPMC7470961 | biostudies-literature
| S-EPMC7397672 | biostudies-literature
| S-EPMC5910428 | biostudies-literature
| S-EPMC10063232 | biostudies-literature
| S-EPMC10370131 | biostudies-literature
| S-EPMC10869892 | biostudies-literature
| S-EPMC7144625 | biostudies-literature