Results 311 to 320 of about 86,859 (350)

A Review of scRNA-seq Imputation Methods

Advances in Computer, Signals and Systems
openaire   +1 more source

SpaGE: Spatial Gene Enhancement using scRNA-seq [PDF]

Nucleic Acids Research, 2020
AbstractSingle-cell technologies are emerging fast due to their ability to unravel the heterogeneity of biological systems. While scRNA-seq is a powerful tool that measures whole-transcriptome expression of single cells, it lacks their spatial localization.
Tamim Abdelaal, Soufiane Mourragui, Ahmed Mahfouz   +2 more
exaly   +6 more sources

Some of the next articles are maybe not open access.

Related searches:

scRNA-seq for Microcephaly Research [III]: Computational Analysis of scRNA-seq Data

2022
Single-cell transcriptomic analysis (scRNA-seq) can enable researchers to explore the gene expression patterns of thousands of individual cells simultaneously. Processing the complex data generated by scRNA-seq requires specialized computational tools.
Benjamin, Babcock, Daniel, Malawsky
openaire   +2 more sources

Mouse heart scRNA-seq

2023
Mouse heart scRNA-seq data of different develop ...
openaire   +1 more source

Integration of scATAC-Seq with scRNA-Seq Data

2022
Single-cell studies are enabling our understanding of the molecular processes of normal cell development and the onset of several pathologies. For instance, single-cell RNA sequencing (scRNA-Seq) measures the transcriptome-wide gene expression at a single-cell resolution, allowing for studying the heterogeneity among the cells of the same population ...
Berest, Ivan, Tangherloni, Andrea
openaire   +3 more sources

Petang_Lab/scRNA-seq-T. vaginalis

These scripts was used to analyse the data for the publication "Single-cell Dissection of Trichomonasvirus-Host Interactions Reveals Viral Load-Driven Phenotypic Heterogeneity in Trichomonas vaginalis" by Luo et al. published in Cell Reports (2025).Send an e-mail to wayneluo0817@gmail.com if you have any questions.
Tang, Petrus, Luo, Hong Wei
openaire   +1 more source

MeRIP-seq/scRNA-seq Code

These are the codes for MeRIP-seq/scRNA-seq analysis used in the paper titled "METTL3-Driven RNA Modifications: A Key Mechanism and Potential Therapeutic Target in Pancreatic Acinar Cell Carcinoma in Mice". The relevant GEO accession numbers are as follows: GSE305529, GSE305530.
Tatekawa, Shotaro, Hara, Tomoaki, Meng, Sikun, Sato, Tetsuya, Ishii, Hideshi   +4 more
openaire   +1 more source