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

Cell Migration01:09

Cell Migration

16.6K
Cell migration, the process by which cells move from one location to another, is essential for the proper development and viability of organisms throughout their life. When cells are not able to migrate properly to their ordained locations, various disorders may occur. For example, disruption in cell migration causes chronic inflammatory diseases such as arthritis.
16.6K
Cell Migration01:19

Cell Migration

6.1K
Cell migration is a process by which the cells move from one location to another, playing an essential role in embryological development, repair and regeneration, immune response, and metastasis. Cells migrate in response to chemical or mechanical signals generated by specific organs or tissues. The overall mechanism includes three steps - polarization, protrusion, and release. Polarization involves the formation of a distinct cell front and rear, which determines the direction of movement.
6.1K

You might also read

Related Articles

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

Sort by
Same author

Activity-dependent adaptive deep brain stimulation improves gait in Parkinson's disease.

Nature medicine·2026
Same author

Validating the ADFSCI hypotension symptom domain as a scalable patient reported outcome measure in spinal cord injury.

NPJ digital medicine·2026
Same author

Mapping the mammalian dark metabolome by <i>in vivo</i> isotope tracing.

bioRxiv : the preprint server for biology·2026
Same author

Comprehensive Curation and Harmonization of Small-Molecule MS/MS Libraries in Spectraverse.

Analytical chemistry·2026
Same author

Language model-guided anticipation and discovery of mammalian metabolites.

Nature·2026
Same author

PID Controlled Epidural Electrical Stimulation for Managing Orthostatic Hypotension in Individuals with Spinal Cord Injury.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A viral ORFeome library for systems-level genetic dissection of host-pathogen interactions.

Cell·2026
Same journal

Co-option of lysosomal machinery shapes the evolution of the intracellular photosymbiosis supporting coral reefs.

Cell·2026
Same journal

LEF1 and niche factors determine T cell stemness across chronic diseases.

Cell·2026
Same journal

Recurrent patterns of TOP1-mediated neuronal genomic damage shared by major neurodegenerative disorders.

Cell·2026
Same journal

Four-dimensional molecular mapping from a spatial snapshot reveals the dynamics of hair follicle organogenesis.

Cell·2026
Same journal

Whole-cell particle-based digital twin simulations from 4D lattice light-sheet microscopy data.

Cell·2026
See all related articles

Related Experiment Video

Updated: May 2, 2026

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

17.9K

A clinical road map for single-cell omics.

Michael A Skinnider1, Gregoire Courtine2, Jocelyne Bloch2

  • 1Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA; Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ, USA.

Cell
|July 11, 2025
PubMed
Summary
This summary is machine-generated.

Single-cell omics, a powerful tool for discovery, faces barriers to clinical use. Overcoming these challenges can enable precise diagnosis and personalized therapies through advanced biomarkers.

Keywords:
machine learningpatient cohortspersonalized medicinesingle-cellspatial transcriptomics

More Related Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.7K
Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy
04:21

Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy

Published on: January 19, 2024

3.0K

Related Experiment Videos

Last Updated: May 2, 2026

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

17.9K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.7K
Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy
04:21

Author Spotlight: Vascular Tissue Dissociation and Exploring Single-Cell Subclusters for Targeted Therapy

Published on: January 19, 2024

3.0K

Area of Science:

  • Biotechnology
  • Genomics
  • Precision Medicine

Background:

  • Single-cell omics has rapidly advanced from a niche technique to a cornerstone of biological research.
  • There is significant potential for single-cell omics to improve clinical diagnostics, disease monitoring, and personalized treatments.
  • Despite its promise, single-cell omics is not yet routinely integrated into clinical decision-making.

Purpose of the Study:

  • To identify and categorize barriers hindering the clinical application of single-cell omics.
  • To explore the potential of single-cell transcriptomics for developing combinatorial biomarkers for clinical decision-making.
  • To propose a framework for identifying patient subgroups and outlining requirements for clinical implementation.

Main Methods:

  • Review and categorization of experimental, computational, and conceptual challenges.
  • Focus on single-cell transcriptomics for biomarker development.
  • Framework development for patient subpopulation identification and clinical readout derivation.

Main Results:

  • Identification of key barriers impeding clinical translation of single-cell omics.
  • Articulation of a strategy for using single-cell transcriptomics to create multi-analyte biomarkers.
  • Outline of requirements for reproducible and actionable clinical data from single-cell omics.

Conclusions:

  • Addressing identified barriers is crucial for clinical adoption of single-cell omics.
  • Combinatorial biomarkers derived from single-cell transcriptomics offer a path toward personalized medicine.
  • A structured approach is needed to translate single-cell omics data into clinically relevant insights.