The technological landscape and applications of single-cell multi-omics
Single-cell multi-omics technologies and methods characterize cell states and activities by
simultaneously integrating various single-modality omics methods that profile the …
simultaneously integrating various single-modality omics methods that profile the …
[HTML][HTML] Computational strategies for single-cell multi-omics integration
Single-cell omics technologies are currently solving biological and medical problems that
earlier have remained elusive, such as discovery of new cell types, cellular differentiation …
earlier have remained elusive, such as discovery of new cell types, cellular differentiation …
Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data
Background A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately
detect the number of cell types in the sample, which can be critical for downstream analyses …
detect the number of cell types in the sample, which can be critical for downstream analyses …
[HTML][HTML] A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization
Genetic screens in cancer cell lines inform gene function and drug discovery. More
comprehensive screen datasets with multi-omics data are needed to enhance opportunities …
comprehensive screen datasets with multi-omics data are needed to enhance opportunities …
OmicsAnalyst: a comprehensive web-based platform for visual analytics of multi-omics data
G Zhou, J Ewald, J ** based on latent subspace learning
The increased availability of high-throughput technologies has enabled biomedical
researchers to learn about disease etiology across multiple omics layers, which shows …
researchers to learn about disease etiology across multiple omics layers, which shows …
Consensus clustering of single-cell RNA-seq data by enhancing network affinity
Y Cui, S Zhang, Y Liang, X Wang… - Briefings in …, 2021 - academic.oup.com
Elucidation of cell subpopulations at high resolution is a key and challenging goal of single-
cell ribonucleic acid (RNA) sequencing (scRNA-seq) data analysis. Although unsupervised …
cell ribonucleic acid (RNA) sequencing (scRNA-seq) data analysis. Although unsupervised …