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 Diversity01:13

Cell Diversity

5.3K
The concept of a cell started with microscopic observations of dead cork tissue by Robert Hooke in 1665. Hooke coined the term "cell" based on the resemblance of the small subdivisions in the cork to the rooms that monks inhabited, called cells. About ten years later, Antonie van Leeuwenhoek became the first person to observe the living and moving cells under a microscope. In the century that followed, the theory that cells represented the basic unit of life developed.
Multicellular...
5.3K
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

8.0K
The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...
8.0K
Frequency-dependent Selection01:21

Frequency-dependent Selection

24.3K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
24.3K
Cellular Differentiation00:57

Cellular Differentiation

5.8K
How does a complex organism such as a human develop from a single cell? It all starts from a single fertilized egg which gives rise to a vast array of cell types, such as nerve cells, muscle cells, and epithelial cells that characterize the adult? Throughout development and adulthood, cellular differentiation leads cells to assume their final morphology and physiology. Differentiation is the process by which unspecialized cells become specialized to carry out distinct functions.
A zygote is a...
5.8K
Types of Selection01:46

Types of Selection

45.5K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
45.5K
Diversity of Antigen Receptors01:28

Diversity of Antigen Receptors

1.8K
Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
Before encountering any antigen, lymphocytes express these receptors. On B cells, the antigen receptor is a membrane-bound antibody molecule called BCR; on T cells, it is a T cell receptor or TCR. B and T cell receptors are composed of two...
1.8K

You might also read

Related Articles

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

Sort by
Same author

The Presence of CD11c+ B Cells with Potent Effector Memory Phenotype in Lung Adenocarcinoma Correlates with Overall Patient Survival.

Cancer immunology research·2026
Same author

Acute Effects of Growth Hormone on the Cellular Immunologic Landscape in Pediatric Patients.

Cureus·2024
Same author

Cancer-associated fibroblasts are the main contributors to epithelial-to-mesenchymal signatures in the tumor microenvironment.

Scientific reports·2023
Same author

Reflecting health: smart mirrors for personalized medicine.

NPJ digital medicine·2019
Same author

Lyme Disease Patient Trajectories Learned from Electronic Medical Data for Stratification of Disease Risk and Therapeutic Response.

Scientific reports·2019
Same author

Precision Medicine for Relapsed Multiple Myeloma on the Basis of an Integrative Multiomics Approach.

JCO precision oncology·2019
Same journal

IL-33 scripts cancer immunity.

Trends in immunology·2026
Same journal

Mitochondrial Ca<sup>2+</sup> signaling: A metabolic rheostat defining tumor and immune cell fate.

Trends in immunology·2026
Same journal

Cross-priming underlies the efficacy of antibody-drug conjugates and immunotherapy combinations.

Trends in immunology·2026
Same journal

Gut microbiome metabolites meet immunometabolism in inflammatory bowel disease.

Trends in immunology·2026
Same journal

Metabolic regulatory nodes of the inflammasome and inflammatory cell death.

Trends in immunology·2026
Same journal

Parental leave in immunology - 6.

Trends in immunology·2026
See all related articles

Related Experiment Video

Updated: Feb 25, 2026

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression
12:52

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression

Published on: April 18, 2021

5.5K

Environments Tune and Select Cellular Diversity.

Brian A Kidd1

  • 1Department of Genetics and Genomic Sciences, Institute for Next Generation Healthcare and Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Trends in Immunology
|August 5, 2017
PubMed
Summary
This summary is machine-generated.

Single-cell sequencing reveals significant gene expression variation between cells. Quantitative models are now identifying the key factors driving this cellular diversity.

More Related Videos

Protein Engineering by Yeast Surface Display
05:49

Protein Engineering by Yeast Surface Display

Published on: November 29, 2024

3.8K
Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
15:00

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

4.4K

Related Experiment Videos

Last Updated: Feb 25, 2026

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression
12:52

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression

Published on: April 18, 2021

5.5K
Protein Engineering by Yeast Surface Display
05:49

Protein Engineering by Yeast Surface Display

Published on: November 29, 2024

3.8K
Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
15:00

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

4.4K

Area of Science:

  • Genomics
  • Systems Biology
  • Molecular Biology

Background:

  • Single-cell sequencing technologies enable high-resolution analysis of cellular heterogeneity.
  • Understanding cell-to-cell variation is crucial for deciphering complex biological systems.

Purpose of the Study:

  • To investigate the drivers of phenotypic diversity using advanced quantitative approaches.
  • To analyze cell-to-cell variation in gene expression from large-scale single-cell sequencing data.

Main Methods:

  • Application of mechanistic and statistical models to single-cell sequencing data.
  • Systems-wide analysis of gene expression levels and variation propagation across cells.

Main Results:

  • Identification of substantial cell-to-cell variation in expression levels.
  • Characterization of how variation propagates between molecules within and across cells.
  • Illumination of key drivers contributing to phenotypic diversity.

Conclusions:

  • Quantitative modeling provides powerful insights into the origins of cellular heterogeneity.
  • Technical advances in single-cell sequencing are key to uncovering biological complexity.