Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Epidemiological profile of respiratory viruses associated with influenza-like illness and severe acute respiratory infection in Guangzhou, China, 2024-2025.

Frontiers in public health·2026
Same author

Corrigendum to Tumor microenvironment assessment-based signatures for predicting response to immunotherapy in non-small cell lung cancer [iScience Volume 29, Issue 3, March 2026, Article e114872].

iScience·2026
Same author

Establishment of In Ovo <i>Salmonella</i> Enteritidis Infection and Synbiotic Delivery Models in Chick Embryos and Their Effects on Early Gut Health.

Animals : an open access journal from MDPI·2026
Same author

Analysis of Epidemiological and Molecular Characteristics of Bocavirus in Guangzhou.

Viruses·2026
Same author

Comparative Metabolomic Analysis of Different Organs of Understory-Transplanted and Wild <i>Dendropanax dentiger</i>.

Metabolites·2026
Same author

CO<sub>2</sub> emission characteristics of hybrid electric vehicles in the tank-to-wheel (TTW) phase in plateau region.

Journal of environmental sciences (China)·2026
Same journal

A Cattle BodyMap of Transcriptome across 52 Tissues and 3 Developmental Stages Reveals New Genetic Insights into Beef Production Traits.

Genomics, proteomics & bioinformatics·2026
Same journal

Real-time Targeted Enrichment in Single-cell Long-read Sequencing.

Genomics, proteomics & bioinformatics·2026
Same journal

Decoding RNA N6-Methyladenosine Methylome of Wheat Using Machine Learning and Nanopore Direct RNA Sequencing.

Genomics, proteomics & bioinformatics·2026
Same journal

Tranquillyzer: A Neural Network Framework for Long-read Annotation and Demultiplexing.

Genomics, proteomics & bioinformatics·2026
Same journal

Advancing Functional Transcriptomics in Zebrafish with High-accuracy Full-length RNA Sequencing.

Genomics, proteomics & bioinformatics·2026
Same journal

NanoRAPID: A Deep Learning-based Framework for Single-molecule RNA Structure Analysis Using Nanopore Direct RNA Sequencing.

Genomics, proteomics & bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Dec 20, 2025

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
05:45

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

3.2K

Deciphering Brain Complexity Using Single-cell Sequencing.

Quanhua Mu1, Yiyun Chen1, Jiguang Wang1

  • 1Department of Chemical and Biological Engineering, Division of Life Science, Center for Systems Biology and Human Health and State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong Special Administrative Region, China.

Genomics, Proteomics & Bioinformatics
|October 7, 2019
PubMed
Summary
This summary is machine-generated.

Single-cell sequencing generates big data to map brain cell types and functions. This technology advances neuroscience, offering new insights into brain development and diseases.

Keywords:
Brain developmentBrain diseasesCell typeNeuroscienceSingle-cell RNA-seq

More Related Videos

Combined Mechanical and Enzymatic Dissociation of Mouse Brain Hippocampal Tissue
07:14

Combined Mechanical and Enzymatic Dissociation of Mouse Brain Hippocampal Tissue

Published on: October 21, 2021

4.5K
Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq
07:49

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Published on: October 26, 2018

9.8K

Related Experiment Videos

Last Updated: Dec 20, 2025

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
05:45

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

3.2K
Combined Mechanical and Enzymatic Dissociation of Mouse Brain Hippocampal Tissue
07:14

Combined Mechanical and Enzymatic Dissociation of Mouse Brain Hippocampal Tissue

Published on: October 21, 2021

4.5K
Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq
07:49

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Published on: October 26, 2018

9.8K

Area of Science:

  • Neuroscience
  • Genomics
  • Computational Biology

Background:

  • The human brain's complexity arises from billions of interconnected cells controlling cognition and behavior.
  • Understanding brain cell types, connectivity, and functions requires analyzing vast amounts of data.
  • Single-cell sequencing technologies profile individual cells to reveal brain complexity.

Purpose of the Study:

  • To review advances in single-cell sequencing methods for brain research.
  • To highlight applications in cell classification, development, and disease mechanisms.
  • To discuss future challenges and opportunities in the field.

Main Methods:

  • Review of experimental and computational single-cell sequencing techniques.
  • Analysis of representative studies applying these technologies to neuroscience.
  • Synthesis of current knowledge and future perspectives.

Main Results:

  • Single-cell sequencing provides a comprehensive view of brain cell diversity.
  • Applications include detailed cell type classification and understanding brain development.
  • Insights into brain disease mechanisms are significantly enhanced.

Conclusions:

  • Big data from single-cell sequencing is revolutionizing neuroscience.
  • This technology is crucial for unraveling complex brain functions and diseases.
  • Continued development promises further breakthroughs in brain research.