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

Network Function of a Circuit01:25

Network Function of a Circuit

533
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.
533
Block Diagram Reduction01:22

Block Diagram Reduction

430
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.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
430
Relation between Mathematical Equations and Block Diagrams01:20

Relation between Mathematical Equations and Block Diagrams

2.7K
In a spring-mass-damper system, the second-order differential equation describes the dynamic behavior of the system. When transformed into the Laplace domain under zero initial conditions, this equation can be effectively analyzed and manipulated. The transformation into the Laplace domain converts differential equations into algebraic equations, simplifying the process of isolating the output.
2.7K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

313
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...
313
Second Uniqueness Theorem01:16

Second Uniqueness Theorem

2.6K
Consider a region consisting of several individual conductors with a definite charge density in the region between these conductors. The second uniqueness theorem states that if the total charge on each conductor and the charge density in the in-between region are known, then the electric field can be uniquely determined.
In contrast, consider that the electric field is non-unique and apply Gauss's law in divergence form in the region between the conductors and the integral form to the surface...
2.6K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.6K
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...
3.6K

You might also read

Related Articles

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

Sort by
Same author

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same author

TaBooN Boolean Network Synthesis Based on Tabu Search.

IEEE/ACM transactions on computational biology and bioinformatics·2021
Same author

Proceedings of the XXXVIIIth Seminar of the French-Speaking Society for Theoretical Biology; Saint-Flour (Cantal), France, 11-13 June, 2018.

Acta biotheoretica·2020
Same author

On Computing Structural and Behavioral Complexities of Threshold Boolean Networks : Application to Biological Networks.

Acta biotheoretica·2019
Same author

Causal Reasoning on Boolean Control Networks Based on Abduction: Theory and Application to Cancer Drug Discovery.

IEEE/ACM transactions on computational biology and bioinformatics·2018
Same author

Extended spiking neural P systems with white hole rules and their red-green variants.

Natural computing·2018

Related Experiment Video

Updated: Dec 16, 2025

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.2K

Bisimilar Booleanization of multivalued networks.

Franck Delaplace1, Sergiu Ivanov1

  • 1IBISC - Paris-Saclay University, Univ. Evry, France.

Bio Systems
|July 6, 2020
PubMed
Summary
This summary is machine-generated.

This study presents a computational method for converting multivalued biological networks into equivalent Boolean networks. This approach bridges the gap between different modeling frameworks, enhancing biological network analysis.

Keywords:
Automatic booleanizationBiological network modellingBisimulationBoolean networkMultivalued network

More Related Videos

Versatile CO2 Transformations into Complex Products: A One-pot Two-step Strategy
07:36

Versatile CO2 Transformations into Complex Products: A One-pot Two-step Strategy

Published on: November 9, 2019

8.3K
RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.3K

Related Experiment Videos

Last Updated: Dec 16, 2025

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.2K
Versatile CO2 Transformations into Complex Products: A One-pot Two-step Strategy
07:36

Versatile CO2 Transformations into Complex Products: A One-pot Two-step Strategy

Published on: November 9, 2019

8.3K
RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.3K

Area of Science:

  • Systems Biology
  • Computational Biology
  • Network Science

Background:

  • Biological networks are modeled using discrete frameworks, primarily Boolean and multivalued networks.
  • Multivalued networks offer greater expressiveness but converting them to Boolean networks with equivalent behavior is challenging.
  • Bridging the gap between these modeling approaches is crucial for comprehensive analysis.

Purpose of the Study:

  • To investigate the theoretical underpinnings of converting multivalued biological networks to Boolean networks.
  • To explore the concept of bisimilar conversion where Boolean integer coding is a modifiable parameter.
  • To develop a computational method for automated inference of bisimilar Boolean networks from multivalued ones.

Main Methods:

  • Theoretical analysis of bisimilar conversion between multivalued and Boolean networks.
  • Investigation of Boolean integer coding as a flexible parameter in the conversion process.
  • Development and application of a computational algorithm for automated network conversion.

Main Results:

  • Established a framework for bisimilar conversion between multivalued and Boolean biological networks.
  • Demonstrated that Boolean integer coding can be freely modified to achieve bisimilarity.
  • Successfully defined a computational method for inferring bisimilar Boolean networks.

Conclusions:

  • The developed computational method effectively infers bisimilar Boolean networks from multivalued ones.
  • This work provides a valuable tool for unifying discrete modeling frameworks in systems biology.
  • The findings facilitate a deeper understanding and analysis of complex regulatory behaviors in biological systems.