Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Protein Networks02:26

Protein Networks

3.7K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.7K
Protein Networks02:26

Protein Networks

1.8K
1.8K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

1.3K
1.3K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

8.2K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
8.2K
Network Function of a Circuit01:25

Network Function of a Circuit

1.1K
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
1.1K
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

4.7K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
4.7K

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

A large language model-based tool for identifying relationships to industry in research on the carcinogenicity of benzene, cobalt, and aspartame.

Environmental health : a global access science source·2025
Same author

Is hate speech detection the solution the world wants?

Proceedings of the National Academy of Sciences of the United States of America·2023
Same author

The epidemiological impact of the Canadian COVID Alert app.

Canadian journal of public health = Revue canadienne de sante publique·2022
Same author

Dilations and degeneracy in network controllability.

Scientific reports·2021
Same author

A Survey of Physics-Based Attack Detection in Cyber-Physical Systems.

ACM computing surveys·2019
Same author

The misinformation machine.

Science (New York, N.Y.)·2019
Same journal

Erratum for the Research Article "Detecting supramolecular organic nanoparticles during heat wave".

Science (New York, N.Y.)·2026
Same journal

Local signals, systemic decline.

Science (New York, N.Y.)·2026
Same journal

The mechanics of liver regeneration.

Science (New York, N.Y.)·2026
Same journal

Computing in a memory with physics.

Science (New York, N.Y.)·2026
Same journal

Retraction.

Science (New York, N.Y.)·2026
Same journal

Making time.

Science (New York, N.Y.)·2026
Ver todos los artículos relacionados
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: May 2, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

2.7K

Perfiles de control de las redes complejas.

Justin Ruths1, Derek Ruths

  • 1Engineering Systems and Design, Singapore University of Technology and Design, Singapore.

Science (New York, N.Y.)
|March 22, 2014
PubMed
Resumen
Este resumen es generado por máquina.

Los investigadores identificaron estructuras de red fundamentales que influyen en las propiedades de control. Una nueva estadística, el perfil de control, revela que las redes del mundo real se agrupan en tres tipos, que difieren de los modelos aleatorios y ofrecen información sobre la organización del sistema.

Más Videos Relacionados

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
07:57

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

8.3K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

1.7K

Videos de Experimentos Relacionados

Last Updated: May 2, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

2.7K
Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
07:57

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

8.3K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

1.7K

Área de la Ciencia:

  • Ciencia de la red Ciencia de la red Ciencia de la red.
  • Ingeniería de Sistemas Ingeniería de Sistemas.
  • Análisis de datos Análisis de datos.

Sus antecedentes:

  • Comprender las propiedades de control de redes complejas es crucial para el diseño del sistema y la modificación del comportamiento.
  • Se sabe que la topología de red se correlaciona con las propiedades de control, pero las estructuras subyacentes requieren una investigación más profunda.

Objetivo del estudio:

  • Para descubrir las estructuras de red fundamentales responsables de la correlación entre la topología y las propiedades de control.
  • Desarrollar una medida cuantitativa para evaluar las estructuras que inducen el control dentro de una red.

Principales métodos:

  • Desarrollo del "perfil de control", una nueva estadística para cuantificar las proporciones de estructuras que influyen en el control.
  • Análisis de perfiles de control a través de varias redes complejas del mundo real.
  • Comparación de perfiles de red del mundo real con los generados por modelos de red al azar estándar.

Principales resultados:

  • Los modelos estándar de redes aleatorias no logran replicar los perfiles de control observados en redes empíricas.
  • Los perfiles de control de redes del mundo real forman tres grupos distintos y bien definidos.
  • Estos grupos sugieren patrones organizativos específicos de alto nivel en sistemas complejos.

Conclusiones:

  • El perfil de control cuantifica efectivamente las estructuras de red relevantes para el control del sistema.
  • El agrupamiento observado de redes del mundo real pone de relieve las desviaciones de los supuestos de redes aleatorias.
  • Los hallazgos proporcionan información sobre la organización funcional y la controlabilidad de sistemas complejos.