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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Ribosome Profiling02:24

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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Related Experiment Video

Updated: Sep 19, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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cellSight: Characterizing dynamics of cells using single-cell RNA-sequencing.

Ranojoy Chatterjee1, Chiraag Gohel1, Brett A Shook2

  • 1Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052.

Biorxiv : the Preprint Server for Biology
|June 6, 2025
PubMed
Summary
This summary is machine-generated.

The automated cellSight workflow streamlines single-cell analysis, reducing manual effort and errors. This enhances data reproducibility and accelerates biological discoveries for improved clinical translation.

Keywords:
BioinformaticsCell interactionIntercellular communicationSingle-cell analysisSoftware

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Single-cell analysis reveals cellular heterogeneity but faces challenges with manual data processing, including inefficiency, errors, and scalability.
  • Manual methods limit the speed and scope of single-cell research, hindering rapid insights and translation.

Purpose of the Study:

  • To introduce cellSight, an automated workflow designed to overcome the limitations of manual data processing in single-cell studies.
  • To provide a user-friendly platform that integrates high-throughput sequencing and automates key analytical tasks.

Main Methods:

  • Development of an automated workflow, cellSight, integrating high-throughput sequencing.
  • Implementation of automated tasks including cell type clustering, feature extraction, and data normalization.
  • Inclusion of standardized analysis pipelines and quality control metrics.

Main Results:

  • cellSight significantly reduces researcher workload, allowing more time for data interpretation and hypothesis generation.
  • The workflow enhances the reproducibility of single-cell data analysis through standardized pipelines and quality control.
  • cellSight's adaptability ensures compatibility with emerging single-cell genomics technologies.

Conclusions:

  • cellSight accelerates the pace of discovery in single-cell biology by automating complex data processing.
  • The platform promotes collaboration and facilitates impactful insights with potential for clinical translation.
  • cellSight offers a scalable and reproducible solution for modern single-cell research.