Contrastive Learning in Single-cell Multiomics Clustering-Reference-Cited by-同舟云学术

Contrastive Learning in Single-cell Multiomics Clustering

Published:2023-09-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
language:
Short-container-title:

Author:

Li Bingjun¹^ORCID,Nabavi Sheida¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3584371.3613010

Reference10 articles.

1. Zhi-Jie Cao and Ge Gao. 2022. Multi-omics single-cell data integration and regulatory inference with graph-linked embedding. Nat. Biotechnol. (2022). Zhi-Jie Cao and Ge Gao. 2022. Multi-omics single-cell data integration and regulatory inference with graph-linked embedding. Nat. Biotechnol. (2022).

2. 10X Genomics. [n. d.]. PBMC from a healthy donor single cell multiome ATAC gene expression demonstration data by Cell Ranger ARC 2.0.0. 10X Genomics. [n. d.]. PBMC from a healthy donor single cell multiome ATAC gene expression demonstration data by Cell Ranger ARC 2.0.0.

3. Bingjun Li and Sheida Nabavi . 2023. A Multimodal Graph Neural Network Framework for Cancer Molecular Subtype Classification. arXiv:2302.12838 ( 2023 ). Bingjun Li and Sheida Nabavi. 2023. A Multimodal Graph Neural Network Framework for Cancer Molecular Subtype Classification. arXiv:2302.12838 (2023).

4. Bingjun Li Tianyu Wang and Sheida Nabavi. 2021. Cancer molecular subtype classification by graph convolutional networks on multi-omics data. In BCB. 1--9. Bingjun Li Tianyu Wang and Sheida Nabavi. 2021. Cancer molecular subtype classification by graph convolutional networks on multi-omics data. In BCB. 1--9.

5. Assessment of computational methods for the analysis of single-cell ATAC-seq data