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Updated: Jul 6, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Resolving cellular dynamics using single-cell temporal transcriptomics.

Yifei Liu¹, Kai Huang¹, Wanze Chen¹

¹Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

Current Opinion in Biotechnology

|January 9, 2024

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Understanding cellular dynamics is key to development and disease. This review covers computational models and live-cell transcriptomics for studying cell state transitions at a single-cell level.

Area of Science:

Cell Biology
Genomics
Bioinformatics

Background:

Cellular dynamics, the study of cell state transitions, is crucial for understanding development and diseases.
Single-cell transcriptomics offers genome-wide insights into these dynamic processes.
Current methods often provide only snapshots, necessitating computational or complementary approaches to infer dynamics.

Purpose of the Study:

To review computational methods for reconstructing cellular dynamics from transcriptomics data.
To discuss the principles, assumptions, and interpretation of these computational models.
To highlight emerging live-cell transcriptomics techniques as a complementary, assumption-free approach.

Main Methods:

Review of computational strategies for inferring cell state trajectories from single-cell RNA sequencing data.

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Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights

Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights

Published on: June 28, 2024

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

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Last Updated: Jul 6, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights

Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights

Published on: June 28, 2024

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

Analysis of methods exploiting temporal information within transcriptomics datasets.

Discussion of nondisruptive live-cell transcriptomics technologies.

Main Results:

Computational models can reconstruct cellular dynamics by analyzing transcriptomic data, either through inherent temporal signals or integrated information.
These models rely on specific assumptions and require careful interpretation.
Live-cell transcriptomics provides direct, assumption-free observations that complement computational predictions.

Conclusions:

Both computational modeling and live-cell transcriptomics are essential for a comprehensive understanding of cellular dynamics.
Integrating these approaches offers a powerful toolkit for studying cell transitions in development and disease.
Future research can leverage these combined methodologies for deeper biological insights.