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

Comparison of network-based pathway analysis methods.

Jason A Papin1, Joerg Stelling, Nathan D Price

  • 1Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive #0412, La Jolla, CA 92093-0412, USA.

Trends in Biotechnology
|July 31, 2004
PubMed
Summary
This summary is machine-generated.

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

A genome-scale metabolic model of a globally disseminated hyperinvasive M1 strain of <i>Streptococcus pyogenes</i>.

mSystems·2024
Same author

Biological and genetic determinants of glycolysis: Phosphofructokinase isoforms boost energy status of stored red blood cells and transfusion outcomes.

Cell metabolism·2024
Same author

A treasure trove of 1034 actinomycete genomes.

Nucleic acids research·2024
Same author

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.

Nature communications·2024
Same author

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions.

mSystems·2024
Same author

Deciphering nutritional stress responses via knowledge-enriched transcriptomics for microbial engineering.

Metabolic engineering·2024
Same journal

A caspase-3-activated protein expression system for apoptosis visualization and apoptosis-pyroptosis conversion to boost antitumor activity.

Trends in biotechnology·2026
Same journal

Over 4 months of ethylene production using solid-state photosynthetic cell factories.

Trends in biotechnology·2026
Same journal

Closing the nitrogen loop in groundwater with biohybrid technologies.

Trends in biotechnology·2026
Same journal

Engineering environmental bacteria for whole-cell PET hydrolysis and assimilation.

Trends in biotechnology·2026
Same journal

Acoustic cavitation-enhanced lymphatic trafficking of inhaled bacterial-sourced biohybrid vaccines for antitumor immunity.

Trends in biotechnology·2026
Same journal

Make uphill thermodynamics downhill in pathway design.

Trends in biotechnology·2026
See all related articles

Network analysis defines biochemical pathways using reaction networks. Comparing elementary modes and extreme pathways in human red blood cells and Helicobacter pylori reveals insights into metabolic network function.

Area of Science:

  • Systems biology and metabolic network analysis.
  • Computational biology and biochemical pathway modeling.

Background:

  • Emergence of network-based definitions for biochemical pathways.
  • Importance of balanced reaction networks in understanding cellular metabolism.
  • Introduction of elementary modes and extreme pathways as key network analysis tools.

Purpose of the Study:

  • To explore the relationship between elementary modes and extreme pathways.
  • To compare these network analysis approaches using real-world metabolic data.
  • To highlight the need for careful interpretation of network properties.

Main Methods:

  • Comparative analysis of elementary modes and extreme pathways.
  • Application to metabolic reconstructions of the human red blood cell (RBC).

Related Experiment Videos

  • Application to metabolic reconstructions of the human pathogen Helicobacter pylori.

    • Main Results:

    • Demonstration of the relationship between elementary modes and extreme pathways.
    • Illustration of how these methods generate novel hypotheses for network function.
    • Identification of the need for careful interpretation of results from realistic metabolic networks.

    Conclusions:

    • Elementary modes and extreme pathways offer complementary views on biochemical network function.
    • Analysis of RBC and H. pylori metabolic networks showcases the utility and interpretation challenges of these methods.
    • Network-based pathway definitions provide powerful frameworks for generating biological hypotheses.