scICML: Information-Theoretic Co-Clustering-Based Multi-View Learning for the Integrative Analysis of Single-Cell Multi-Omics Data
Author:
Affiliation:
1. Institute of Mathematical Sciences, Shanghaitech University, Shanghai, China
2. Department of Statistics, The Chinese University of Hong Kong, Hong Kong, SAR, China
Funder
Chinese University of Hong Kong
Chinese University of Hong Kong Science Faculty's Direct Research
Chinese University of Hong Kong Science Faculty's Collaborative Research Impact Matching Scheme
Hong Kong Research Grant Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Genetics,Biotechnology
Link
http://xplorestaging.ieee.org/ielx7/8857/10422871/10223274.pdf?arnumber=10223274
Reference43 articles.
1. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity
2. scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells
3. Joint profiling of chromatin accessibility and gene expression in thousands of single cells
4. Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity
5. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell
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