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Related Concept Videos

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
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Block Diagram Reduction01:22

Block Diagram Reduction

The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
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Decision Making: P-value Method

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Related Experiment Videos

Adaptive intervention in probabilistic boolean networks.

Ritwik Layek1, Aniruddha Datta, Ranadip Pal

  • 1Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77843, USA.

Bioinformatics (Oxford, England)
|June 10, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces on-line adaptive control for gene regulatory networks, improving therapeutic intervention strategies. Adaptive designs enhance performance even with imperfect models, offering a more robust approach for systems biology.

Related Experiment Videos

Area of Science:

  • Translational Systems Biology
  • Control Theory
  • Computational Biology

Background:

  • Designing therapeutic interventions for gene regulatory networks (GRNs) is crucial for altering cellular dynamics.
  • Current methods often rely on accurate network models, which are challenging to obtain for GRNs due to complexity and limited data.
  • Inaccurate models can lead to suboptimal intervention strategies.

Purpose of the Study:

  • To demonstrate the feasibility of on-line adaptive control for improving intervention performance in GRNs.
  • To develop intervention strategies that do not require accurate full-model inference.
  • To enhance the robustness of therapeutic designs in the face of model uncertainties.

Main Methods:

  • Application of on-line adaptive control to genetic regulatory networks modeled by probabilistic Boolean networks (PBNs).
  • Simulations were used to evaluate the performance of adaptive designs.
  • Development of two algorithms tailored for different PBN characteristics (instantaneously random and context-sensitive).

Main Results:

  • On-line adaptive control significantly improves intervention performance in PBN-modeled GRNs.
  • Adaptive designs yield better results in terms of average cost compared to non-adaptive methods.
  • The proposed algorithms show effectiveness for specific types of PBNs.

Conclusions:

  • On-line adaptive control is a feasible and effective approach for designing therapeutic interventions in GRNs.
  • Adaptive strategies offer improved performance and robustness, even with incomplete or uncertain network models.
  • This work provides a more practical framework for applying control theory to biological systems.