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Learn about small conditional RNA (scRNA), a type of engineered RNA molecule that can interact and change conformation in response to inputs. See examples of scRNA signal transduction for biological research and medical applications.
Learn about the techniques and applications of single-cell sequencing, which examines the nucleic acid sequence information from individual cells. Find out how single-cell sequencing can reveal cellular differences, functions, and variability in various fields such as cancer, development, and microbiology.
Single-cell RNA sequencing (scRNA-seq) technology has become the state-of-the-art approach for unravelling the heterogeneity and complexity of RNA transcripts within individual cells, as well as revealing the composition of different cell types and functions within highly organized tissues/organs/or …
The rapid rise of single-cell RNA sequencing (scRNA-seq) means researchers can find reviews 1,2,3 and evolving resources such as Single-Cell Best Practices.The book, co-authored by members of the ...
Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell ...
Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at ...
However, the rapidly evolving field of scRNA-seq invoked the emergence of various analytics approaches aimed to maximize the full potential of this novel strategy. Unlike population-based RNA sequencing approaches, scRNA seq necessitates comprehensive computational tools to address high data complexity and keep up with the emerging single-cell ...
Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and ...
Prior to scRNA-seq, transcriptome analysis was performed using bulk RNA-seq, which is a straight-forward method for comparing the averages of cellular expression. This can be the best choice of method if looking for disease biomarkers or not expecting or not concerned with a lot of cellular heterogeneity in the sample.
In summary, scRNA-seq is a powerful tool that will allow researchers to address human brain complexity by identifying cell subpopulations and elucidating specific functions. scRNA-seq has a higher resolution than bulk RNA-seq and allows us to better understand cellular heterogeneity and how it changes during dynamic processes, such as ...