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Self|supervised contrastive learning for integrative single cell RNA ...


Self-supervised contrastive learning for integrative single cell RNA ...

We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data representation and the ...

Self-supervised contrastive learning for integrative single cell RNA ...

We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data ...

Self-supervised contrastive learning for integrative single cell RNA ...

Here, we present a self-supervised Contrastive LEArning framework for scRNA-seq (CLEAR) profile representation and the downstream analysis.

[PDF] Self-supervised contrastive learning for integrative single cell ...

Self-supervised contrastive learning for integrative single cell RNA-seq data analysis · Wenkai Han, Yuqi Cheng, +7 authors. Yu Li · Published in Briefings ...

CLEAR: Self-supervised contrastive learning for integrative ... - GitHub

CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis - ml4bio/CLEAR.

Self-supervised contrastive learning for integrative single cell RNA ...

Abstract. We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data representation a.

Integrating large-scale single-cell RNA sequencing in central ...

In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data.

Self-supervised contrastive learning for integrative single cell RNA ...

The proposed method successfully identifies and illustrates inflammatory-related mechanisms in a COVID-19 disease study with 43695 single cells from ...

Self-supervised contrastive learning for integrative single cell RNA-seq

et al. Single-cell RNA-Seq profiling of human preimplantation embryos and. 46 embryonic stem cells. Nature structural & molecular biology 20, ...

Self-supervised contrastive learning for integrative single cell RNA ...

Abstract We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data representation and ...

Contrastive learning enables rapid mapping to multimodal single ...

Here we present contrastive learning of cell representations, Concerto, which leverages a self-supervised distillation framework to model multimodal single- ...

Contrastive self-supervised clustering of scRNA-seq data

Single-cell RNA sequencing (scRNA-seq) has emerged has a main strategy to study transcriptional activity at the cellular level.

Self-supervised contrastive learning for integrative single cell RNA ...

Abstract We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data ...

Self-supervised contrastive learning for integrative single cell RNA ...

AbstractSingle-cell RNA-sequencing (scRNA-seq) has become a powerful tool to reveal the complex biological diversity and heterogeneity among cell ...

scRNA-seq Data Clustering by Cluster-aware Iterative Contrastive ...

Self-supervised contrastive learning for integrative single cell rna-seq data analysis. Briefings in Bioinformatics, 23(5):bbac377, 2022. He ...

Self-supervised contrastive learning for integrative single cell RNA ...

Abstract Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool to reveal the complex biological diversity and heterogeneity ...

ScCCL: Single-Cell Data Clustering Based on Self-Supervised ...

The growing maturity of single-cell RNA-sequencing (scRNA ... ScCCL: Single-Cell Data Clustering Based on Self-Supervised Contrastive Learning.

Benchmarking Self-Supervised Learning for Single-Cell Data

Self-supervised contrastive learning for integrative single cell RNA-seq data analysis. Article. Full-text available. Sep 2022. Wenkai Han ...

Large-Scale Cell Representation Learning via Divide-and-Conquer ...

Self-supervised contrastive learning for integrative single cell rna-seq data analysis. Briefings in Bioinformatics, 23, 2021. [33] Zhenyu ...

Miscell: An efficient self-supervised learning approach for dissecting ...

Comprehensive analysis of single-cell RNA-seq (scRNA-seq) is helpful ... contrastive loss of the original single-cell and its corresponding ...