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

Design Example01:23

Design Example

308
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
308
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

6.3K
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...
6.3K
Cellular Differentiation00:57

Cellular Differentiation

2.5K
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...
2.5K
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

3.1K
A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
3.1K
Overview of Cell Signaling01:23

Overview of Cell Signaling

19.8K
Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
Cells respond to many types of information, often through receptor proteins positioned on the membrane. For example, skin cells respond to and transmit touch...
19.8K

You might also read

Related Articles

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

Sort by
Same author

Growth control as a central regulator for tuning the cellular context.

Journal of biological engineering·2026
Same author

Biocomputation: Moving Beyond Turing with Living Cellular Computers.

Communications of the ACM·2026
Same author

Parameter Evolvability in Gene Expression Models Drives Phenotypic Adaptation.

ALIFE : proceedings of the artificial life conference. International Conference on Artificial Life·2026
Same author

Automated workflow for genotyping individual transposon library variants.

BMC methods·2026
Same author

Dynamics of genetic circuits in Pseudomonas protegens.

Cell systems·2026
Same author

Exploring the computing power of microbes that shapes the environment.

Current opinion in microbiology·2026
Same journal

Editorial for special issue "When should mathematical models be used in biology".

Seminars in cell & developmental biology·2026
Same journal

Conserved machinery, divergent functions: evolutionary plasticity of the STK36/ULK4 kinase complex in ciliogenesis and signaling.

Seminars in cell & developmental biology·2026
Same journal

Chemical biology tools for studying tissue development.

Seminars in cell & developmental biology·2026
Same journal

Tetrahymena as a model organism for cilia research.

Seminars in cell & developmental biology·2026
Same journal

Emerging Concepts in Cardiovascular Development and Regeneration.

Seminars in cell & developmental biology·2026
Same journal

Endothelial origin of hematopoietic stem cells: Insights from new technologies and unresolved questions.

Seminars in cell & developmental biology·2026
See all related articles

Related Experiment Video

Updated: May 9, 2025

Rapid Development of Cell State Identification Circuits with Poly-Transfection
09:21

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Published on: February 24, 2023

1.3K

Why cellular computations challenge our design principles.

Lewis Grozinger1, Bruno Cuevas-Zuviría2, Ángel Goñi-Moreno1

  • 1Systems Biology Department, Centro Nacional de Biotecnologia (CNB), CSIC, Darwin 3, Madrid 28049, Spain.

Seminars in Cell & Developmental Biology
|May 1, 2025
PubMed
Summary
This summary is machine-generated.

Synthetic biologists engineer biological systems for computation. This research explores how natural biological computation principles can inform the design of advanced cellular computations, diverging from traditional computing methods.

Keywords:
BiocomputationCellular computingComplexitySynthetic biology

More Related Videos

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
10:32

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Published on: April 15, 2015

8.4K
Silicon Microchips for Manipulating Cell-cell Interaction
23:21

Silicon Microchips for Manipulating Cell-cell Interaction

Published on: August 30, 2007

10.7K

Related Experiment Videos

Last Updated: May 9, 2025

Rapid Development of Cell State Identification Circuits with Poly-Transfection
09:21

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Published on: February 24, 2023

1.3K
Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
10:32

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

Published on: April 15, 2015

8.4K
Silicon Microchips for Manipulating Cell-cell Interaction
23:21

Silicon Microchips for Manipulating Cell-cell Interaction

Published on: August 30, 2007

10.7K

Area of Science:

  • Synthetic biology
  • Computational theory
  • Bio-computation

Background:

  • Biological systems naturally perform computations.
  • Synthetic biology aims to engineer biological systems for computational tasks, often mimicking silicon-based computer design.
  • Natural biological computation evolved differently from conventional computing principles.

Purpose of the Study:

  • To explore concepts connecting computational theory, living cells, and computers.
  • To provide insights for developing sophisticated biological computations.
  • To highlight the unique potential of biological computers in specific niches.

Main Methods:

  • Conceptual exploration of computational theory and biological systems.
  • Analysis of natural evolution of biological computation.
  • Comparison of conventional and biological computing paradigms.

Main Results:

  • Biological computers can outperform conventional computers in specific domains.
  • Biocomputation does not need to replicate electronic computation capabilities.
  • Intelligently designed cellular computations will differ from traditional computing.

Conclusions:

  • Re-engineering biology for computation should leverage life's evolved principles.
  • Cellular computations will diverge in implementation and application from traditional computing.
  • Understanding natural biological computation is key for future advancements.