Unsupervised manifold alignment for single-cell multi-omics data-Reference-Cited by-同舟云学术

Unsupervised manifold alignment for single-cell multi-omics data

Published:2020-09-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
language:
Short-container-title:

Author:

Singh Ritambhara¹,Demetci Pinar²,Bonora Giancarlo³,Ramani Vijay⁴,Lee Choli³,Fang He⁵,Duan Zhijun⁶,Deng Xinxian⁵,Shendure Jay⁷,Disteche Christine⁵,Noble William Stafford⁸

Affiliation:

1. Department of Computer Science, Center for Computational Molecular, Biology, Brown University

2. Center for Computational Molecular, Biology, Brown University

3. Department of Genome Sciences, University of Washington

4. UC San Francisco

5. Department of Pathology, University of Washington

6. Division of Hematology, University of Washington

7. Howard Hughes Medical Institute, Department of Genome Sciences, University of Washington

8. Department of Genome Sciences,University of Washington, Paul G. Allen School of Computer Science and Engineering, University of Washington

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3388440.3412410

Reference18 articles.

1. J. Cao J. S. Packer V. Ramani D. A. Cusanovich C. Huynh R. Daza X. Qiu C. Lee S. N. Furlan F. J. Steemers etal 2017. Comprehensive single-cell transcriptional profiling of a multicellular organism. Science 357 6352 (2017) 661--667. J. Cao J. S. Packer V. Ramani D. A. Cusanovich C. Huynh R. Daza X. Qiu C. Lee S. N. Furlan F. J. Steemers et al. 2017. Comprehensive single-cell transcriptional profiling of a multicellular organism. Science 357 6352 (2017) 661--667.

2. K. Cao X. Bai Y. Hong and L. Wan. 2020. Unsupervised Topological Alignment for Single-Cell Multi-Omics Integration. bioRxiv (2020). https://doi.org/10.1101/2020.02.02.931394. K. Cao X. Bai Y. Hong and L. Wan. 2020. Unsupervised Topological Alignment for Single-Cell Multi-Omics Integration. bioRxiv (2020). https://doi.org/10.1101/2020.02.02.931394.

3. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell

4. N. Cristianini and J. Shawe-Taylor. 2000. An Introduction to Support Vector Machines. Cambridge UP Cambridge UK. N. Cristianini and J. Shawe-Taylor. 2000. An Introduction to Support Vector Machines. Cambridge UP Cambridge UK.

Cited by 42 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. scCross: a deep generative model for unifying single-cell multi-omics with seamless integration, cross-modal generation, and in silico exploration;Genome Biology;2024-07-29

2. A Commentary on Multi-omics Data Integration in Systems Vaccinology;Journal of Molecular Biology;2024-04

3. Deep Learning in Single-cell Analysis;ACM Transactions on Intelligent Systems and Technology;2024-03-29

4. Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS;Nature Biotechnology;2024-01-23

5. Benchmarking multi-omics integration algorithms across single-cell RNA and ATAC data;Briefings in Bioinformatics;2024-01-22