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Single-Cell RNA Sequencing (scRNA-Seq) Data Analysis of Retinal Homeostasis and Degeneration of Microglia
Single-cell RNA sequencing (scRNA-seq) experiment reveals previously unseen molecular features. The number of sequencing procedures and computational...
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Single Cell RNA-Sequencing in Arabidopsis Root Tissues
Droplet-based single-cell RNA-sequencing (scRNA-seq)Single-cell RNA-sequencing (scRNA-seq) empowers transcriptomicTranscriptomics profiling with an...
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Identification of TIMPs signatures in Randall plaque from single-cell RNA sequencing (scRNA-Seq) analysis
BackgroundTissue inhibitors of metalloproteinases (TIMPs) are essential for controlling the dynamics of the extracellular matrix. Although their role...
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Integration of scATAC-Seq with scRNA-Seq Data
Single-cell studies are enabling our understanding of the molecular processes of normal cell development and the onset of several pathologies. For...
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Single-Cell Sequencing of 3′ RNA Transcripts
Single-cell RNA sequencing (scRNA-seq) enables the measurement of RNA expressed from individual cells within a tissue or population. RNA expression...
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Preparation of Drosophila Ovarioles for Single-Cell RNA Sequencing
The production of eggs in the Drosophila ovary requires complex interactions between multiple cell types that coexist within the same solid tissue....
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Comparison of cell type distribution between single-cell and single-nucleus RNA sequencing: enrichment of adherent cell types in single-nucleus RNA sequencing
Single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) is an effective technique for estimating the cellular composition and transcriptional...
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Data Analysis Pipeline for scRNA-seq Experiments to Study Early Oogenesis
Germ cells as the means for the transmission of genetic information between generations have been a hot topic of research for decades. The analysis...
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scRNA-seq for Microcephaly Research [I]: Single-Cell Droplet Encapsulation, mRNA Capture, and cDNA Synthesis
Single-cell RNA sequencing (scRNA-seq) allows for the transcriptomic profiling of a sample tissue with single-cell resolution. The concept of...
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Advancing ScRNA-Seq Data Integration via a Novel Gene Selection Method
Cancer presents a formidable challenge in medical research, spurring efforts to demystify its underlying mechanisms towards advancing precision...
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scRNA-seq for Microcephaly Research [III]: Computational Analysis of scRNA-seq Data
Single-cell transcriptomic analysis (scRNA-seq) can enable researchers to explore the gene expression patterns of thousands of individual cells...
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LAST-seq: single-cell RNA sequencing by direct amplification of single-stranded RNA without prior reverse transcription and second-strand synthesis
Existing single-cell RNA sequencing (scRNA-seq) methods rely on reverse transcription (RT) and second-strand synthesis (SSS) to convert...
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Full-Length Single-Cell RNA-Sequencing with FLASH-seq
The single-cell RNA-sequencing (scRNA-seq) field has evolved tremendously since the first paper was published back in 2009 (Tang et al. Nat Methods...
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Cell-type-specific co-expression inference from single cell RNA-sequencing data
The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types,...
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Single-cell RNA sequencing opens a new era for cotton genomic research and gene functional analysis
Single-cell RNA sequencing (scRNA-seq) is one of the most advanced sequencing technologies for studying transcriptome landscape at the single-cell...
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cnnImpute: missing value recovery for single cell RNA sequencing data
The advent of single-cell RNA sequencing (scRNA-seq) technology has revolutionized our ability to explore cellular diversity and unravel the...
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Advancements in Single-Cell RNA Sequencing Research for Neurological Diseases
Neurological diseases are a major cause of the global burden of disease. Although the mechanisms of the occurrence and development of neurological...
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scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly...
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Advancing skeletal health and disease research with single-cell RNA sequencing
Orthopedic conditions have emerged as global health concerns, impacting approximately 1.7 billion individuals worldwide. However, the limited...
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Exploring the advances of single-cell RNA sequencing in thyroid cancer: a narrative review
Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial increase in occurrence in recent decades. To gain a...
