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 Experiment Videos

A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions.

Andreas Kremling1, Sophia Fischer, Kapil Gadkar

  • 1Systems Biology Group, Max-Planck-Institut für Dynamik komplexer technischer Systeme, 39106 Magdeburg, Germany. kremling@mpi-magdeburg.mpg.de

Genome Research
|September 3, 2004
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

WILDkCAT: Extract, retrieve, and predict enzyme turnover numbers of constraint-based metabolic models.

Bioinformatics (Oxford, England)·2026
Same author

K-Ras controls asymmetric cell divisions from the primary cilium.

Cell death & disease·2026
Same author

EpiATLAS - a reference for human epigenomic research.

bioRxiv : the preprint server for biology·2026
Same author

ZFHX4 is necessary for dopaminergic neuron differentiation and controls cell cycle by regulating LIN28A.

Stem cell reports·2026
Same author

A hierarchical network model for the estimate of the energy expenditure in individuals with type 1 diabetes.

Engineering applications of artificial intelligence·2026
Same author

Going beyond size: exploring the metabolic burden in <i>Pseudomonas putida</i> during heterologous protein production.

Synthetic biology (Oxford, England)·2026

This study presents a benchmark for analyzing biochemical networks using experimental data. It focuses on designing new experiments to distinguish between different biological models, aiding in systems biology research.

Area of Science:

  • Systems Biology
  • Biochemical Engineering
  • Computational Biology

Background:

  • Analyzing complex biochemical networks from experimental data is challenging.
  • Bioreactor systems provide a controlled environment for studying organism growth and intracellular components.
  • Model discrimination is crucial when multiple models fit the same data.

Purpose of the Study:

  • To establish a benchmark problem for reconstructing and analyzing biochemical networks.
  • To address challenges in reverse engineering, parameter estimation, and identifiability of biological models.
  • To focus on model discrimination using bioreactor control inputs.

Main Methods:

  • Utilizing sampled experimental data from a bioreactor system.
  • Applying methods for reverse engineering and parameter estimation of biochemical networks.

Related Experiment Videos

  • Designing new experiments, specifically manipulating feed rate and feed concentration, for model discrimination.

    • Main Results:

    • A benchmark problem is defined for biochemical network reconstruction and analysis.
    • The study addresses parameter estimation and identifiability issues.
    • Methods for discriminating between model variants using bioreactor control inputs are discussed.

    Conclusions:

    • The benchmark facilitates the evaluation of methods for biochemical network analysis.
    • Effective model discrimination strategies are essential for advancing systems biology.
    • Interactive web resources are provided to verify calculated input profiles.