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Related Concept Videos

Deactivation Processes: Jablonski Diagram01:25

Deactivation Processes: Jablonski Diagram

Luminescence, the emission of light by a substance that has absorbed energy, is a process that involves the interaction of molecules with light. The energy-level diagram, or Jablonski diagram, is a graphical representation of these interactions, illustrating the various states and transitions a molecule can undergo. In a typical Jablonski diagram, the lowest horizontal line represents the ground-state energy of the molecule, which is usually a singlet state. This state represents the energies...
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Network Function of a Circuit

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.
Block Diagram Reduction01:22

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Circuit Terminology01:14

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
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meta-Directing Deactivators: –NO2, –CN, –CHO, –⁠CO2R, –COR, –CO2H01:13

meta-Directing Deactivators: –NO2, –CN, –CHO, –⁠CO2R, –COR, –CO2H

All meta-directing substituents are deactivating groups. These substituents withdraw electrons from the aromatic ring, making the ring less reactive toward electrophilic substitution. For example, the nitration of nitrobenzene is 100,000 times slower than that of benzene because of the deactivating effect of the nitro group. The first step in an electrophilic aromatic substitution is the addition of an electrophile to form a resonance-stabilized carbocation. The energy diagrams for the...
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Continuity of a Function

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Related Experiment Video

Updated: Jun 1, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Functionality and metagraph disintegration in boolean networks.

Jamie X Luo1, Matthew S Turner

  • 1Centre for Complexity Science, University of Warwick, Coventry CV4 7AL, UK.

Journal of Theoretical Biology
|May 24, 2011
PubMed
Summary
This summary is machine-generated.

Genetic regulatory network complexity, measured by function duration (T), exponentially decreases the number of possible networks and their mutation robustness. This suggests limits on typical network complexity, though some networks may scale exponentially with gene number (N).

Related Experiment Videos

Last Updated: Jun 1, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

  • Systems Biology
  • Computational Biology
  • Evolutionary Genetics

Background:

  • Gene regulatory networks (GRNs) control cellular functions through complex interactions.
  • Understanding the relationship between network structure, function, and evolutionary constraints is crucial.
  • Boolean models represent gene expression as discrete states (on/off).

Purpose of the Study:

  • To investigate how functional complexity, defined by temporal expression profiles (T), constrains genetic regulatory networks.
  • To analyze the impact of functional complexity on network evolution and robustness to mutations.
  • To explore network properties for different expression space topologies (linear, stars, trees).

Main Methods:

  • Mathematical modeling of Boolean gene regulatory networks.
  • Parameterization of functional complexity by duration (T) of a vector expression profile v(t).
  • Analysis of network counts, mutation robustness, and evolutionary landscape dynamics.

Main Results:

  • The number of networks generating a function decreases exponentially with complexity (T).
  • Network robustness to mutations weakens as functional complexity increases.
  • Functional complexity drives a 'metagraph disintegration effect', altering evolutionary pathways.

Conclusions:

  • Functional complexity imposes significant constraints on genetic regulatory networks and their evolution.
  • Typical network complexity is limited polynomially by gene number (N), with exceptions scaling exponentially.
  • Evolutionary history and functional complexity shape the accessible evolutionary landscape for species.