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

You might also read

Related Articles

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

Sort by
Same author

Cavity control of multiferroic order in single-layer NiI<sub>2</sub>.

npj computational materials·2026
Same author

IRF2 is an essential transcription factor with pathogenic and prognostic impact in multiple myeloma.

Blood·2026
Same author

Multiple photon field-induced topological states in bulk HgTe.

Science advances·2026
Same author

Foundation models and deep learning for cancer drug response prediction: a framework for data, metrics, and validation.

Briefings in bioinformatics·2026
Same author

Field-resolved observation of exciton coherence in a van der Waals magnet.

Nature materials·2026
Same author

Purcell enhancement of directional edge photocurrent in a van der Waals self-cavity.

Nature communications·2026

Related Experiment Video

Updated: May 2, 2026

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.1K

Advances in network-based metabolic pathway analysis and gene expression data integration.

Alberto Rezola, Jon Pey, Luis Tobalina

    Briefings in Bioinformatics
    |March 15, 2014
    PubMed
    Summary
    This summary is machine-generated.

    Recent advances in computational methods enable network-based metabolic pathway analysis for large-scale biological networks. This review details novel techniques for computing elementary flux modes and integrating metabolic pathways with gene expression data.

    Keywords:
    constraint-based modellingelementary flux modesgene expression datagenome-scale metabolic networksnetwork-based metabolic pathway analysis

    More Related Videos

    Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
    03:08

    Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

    Published on: October 3, 2025

    1.1K
    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
    05:01

    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

    Published on: July 1, 2020

    4.7K

    Related Experiment Videos

    Last Updated: May 2, 2026

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
    07:11

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

    Published on: November 10, 2023

    3.1K
    Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
    03:08

    Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

    Published on: October 3, 2025

    1.1K
    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
    05:01

    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

    Published on: July 1, 2020

    4.7K

    Area of Science:

    • Systems Biology
    • Metabolic Engineering
    • Bioinformatics

    Background:

    • Metabolic networks have introduced novel mathematical pathway concepts beyond traditional maps.
    • Interpreting 'omics' data with network-based pathways has been computationally challenging for genome-scale networks.

    Purpose of the Study:

    • To review recent progress in network-based metabolic pathway analysis.
    • To highlight novel optimization techniques for computing elementary flux modes.
    • To summarize methods for integrating metabolic pathways with gene expression data.

    Main Methods:

    • Review of recent literature on network-based metabolic pathway analysis.
    • Detailed examination of optimization techniques for elementary flux modes computation.
    • Summary of approaches for integrating gene expression data with metabolic pathways.

    Main Results:

    • Significant progress has been made in computing elementary flux modes for large metabolic networks.
    • Novel computational approaches now make network-based pathway analysis feasible for genome-scale networks.
    • Advances facilitate the integration of gene expression data with metabolic pathway concepts.

    Conclusions:

    • Network-based pathway analysis is becoming increasingly viable for large-scale biological data.
    • New computational tools enhance the interpretation of metabolic networks and gene expression data.
    • This field holds significant promise for advancing systems biology and metabolic engineering.