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Single Cell RNA Sequencing in NASH

2022
Single cell RNA sequencing (scRNA-seq) allows to uncover cellular heterogeneity and the identification of novel subpopulations. In non-alcoholic steatohepatitis (NASH), scRNA-seq is particularly powerful to understand non-parenchymal cell heterogeneity in the liver, e.g. for inflammatory cells.
Jana Hundertmark   +2 more
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Single-cell RNA sequencing in pancreatic cancer

Nature Reviews Gastroenterology & Hepatology, 2021
The application of single-cell RNA sequencing platforms has generated notable insights into the heterogeneity underlying pancreatic ductal adenocarcinoma (PDAC), encompassing both the neoplastic compartment and the tumour microenvironment. In this Comment, we discuss the most pertinent findings gleaned from both mouse models and human PDAC samples, as ...
Jincheng Han   +2 more
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Introduction to Single‐Cell RNA Sequencing

Current Protocols in Molecular Biology, 2018
AbstractDuring the last decade, high‐throughput sequencing methods have revolutionized the entire field of biology. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA‐seq) has fueled many important discoveries and is now a routine method in biomedical research. However, RNA‐seq is typically performed in “bulk,” and
Thale Kristin, Olsen, Ninib, Baryawno
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Single-cell RNA sequencing: An overview for the ophthalmologist

Seminars in Ophthalmology, 2021
Understanding the molecular composition of pathogenic tissues is a critical step in understanding the pathophysiology of disease and designing therapeutics. First described in 2009, single cell RNA sequencing (scRNAseq) is a methodology whereby thousands of cells are simultaneously isolated into individual micro-environments that can be altered ...
Elizabeth J. Rossin   +2 more
openaire   +2 more sources

Single‐Cell RNA Sequencing in Hematological Diseases

PROTEOMICS, 2020
Abstract Hematological diseases, including leukemia, lymphoma, and multiple myeloma, are characterized by high heterogeneity with diverse cellular subpopulations. Single‐cell RNA sequencing (scRNA‐seq), a transformational technology, provides deep insights into cell‐to‐cell variation in tumor and microenvironment, allows high ...
Yue Zhu   +4 more
openaire   +2 more sources

Single-Cell RNA Sequencing with Drop-Seq

2019
Drop-Seq is a low-cost, high-throughput platform to profile thousands of cells by encapsualting them into individual droplets. Uniquely barcoded mRNA capture microparticles and cells are coconfined through a microfluidic device within the droplets where they undergo cell lysis and RNA hybridiztion. After breaking the droplets and pooling the hybridized
Josephine, Bageritz, Gianmarco, Raddi
openaire   +2 more sources

Single-Cell RNA Sequencing of Glioblastoma Cells

2018
Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when
Rajeev, Sen   +5 more
openaire   +2 more sources

Preparation of single cells from tumors for single-cell RNA sequencing

2020
Intratumoral heterogeneity of cancer cells and tumor-infiltrating immune cells is increasingly being viewed as a key factor driving tumor progression and response to therapy. Over the past several years, technological advances have created powerful tools to analyze the tumor microenvironment on a single-cell level, including mass cytometry and single ...
Yonina, Bykov   +2 more
openaire   +2 more sources

Depletion of Ribosomal RNA Sequences from Single‐Cell RNA‐Sequencing Library

Current Protocols in Molecular Biology, 2016
AbstractRecent advances in single‐cell RNA sequencing technologies have revealed high heterogeneity of gene expression profiles in individual cells. However, most current single‐cell RNA‐seq methods use oligo‐dT priming in the reverse transcription steps and detect only polyA‐positive for more accuracy, since there are also polyA‐positive non‐coding ...
Nan, Fang, Rumeysa, Akinci-Tolun
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