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

Effect and influencing factors of early ileostomy closure 2-4 weeks on patients with rectal cancer.

Frontiers in oncology·2026
Same author

Comparative physiological and transcriptome analyzes reveal the function of exogenous dopamine in improving the tolerance to salt stress in <i>Vitis vinifera</i> L.

Frontiers in plant science·2026
Same author

Co-administration of recombinant Pichia pastoris-CXCL20a and immunostimulatory polysaccharides enhances resistance to Aeromonas hydrophila in grass carp (Ctenopharyngodon idella).

Fish & shellfish immunology·2026
Same author

Tumor microenvironment-driven mechanisms of photodynamic therapy resistance and emerging targeted combination strategies.

Journal of photochemistry and photobiology. B, Biology·2026
Same author

First human decedent model of orthotopic multi-organ xenotransplantation: Whole liver and bilateral kidneys from a six-gene-edited pig.

Med (New York, N.Y.)·2026
Same author

Site-specific methylation of a TLR1 promoter SNP impedes CREB binding to impair antibacterial immunity in grass carp.

Journal of immunology (Baltimore, Md. : 1950)·2026

Related Experiment Video

Updated: Dec 28, 2025

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

4.2K

FastMM: an efficient toolbox for personalized constraint-based metabolic modeling.

Gong-Hua Li1, Shaoxing Dai1, Feifei Han2

  • 1State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.

BMC Bioinformatics
|February 23, 2020
PubMed
Summary
This summary is machine-generated.

FastMM is a new C/C++ toolbox that significantly accelerates constraint-based metabolic modeling, offering a user-friendly solution for large-scale genome-wide analysis and personalized medicine applications.

Keywords:
Constraint-based modelFastMMMetabolic modelingMetabolism

More Related Videos

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
An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

4.1K

Related Experiment Videos

Last Updated: Dec 28, 2025

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

4.2K
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
An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

4.1K

Area of Science:

  • Computational biology
  • Systems biology
  • Metabolic modeling

Background:

  • Constraint-based metabolic modeling aids in understanding disease mechanisms, drug target identification, and biomarker discovery.
  • Current tools like COBRA 3.0, while powerful, face computational time limitations for large-scale analyses.

Purpose of the Study:

  • To develop a faster and more efficient toolbox for constraint-based metabolic modeling.
  • To overcome the computational bottlenecks of existing software for genome-wide analyses.

Main Methods:

  • Rewriting COBRA 3.0's core functionalities in C/C++ to create the FastMM toolbox.
  • Developing a compatible Matlab/Octave interface for enhanced usability and accessibility.
  • Implementing advanced features like multi-threading for complex modeling tasks.

Main Results:

  • FastMM demonstrates significant speed improvements (2-400x for FBA and knockout analyses, 8x for MCMC) compared to COBRA 3.0.
  • The toolbox provides consistent outputs and outperforms other metabolic modeling tools like Cobrapy and Fast-SL.
  • FastMM enables large-scale personalized metabolic modeling, including analysis of individual cancer metabolic profiles from datasets like TCGA.

Conclusions:

  • FastMM offers an efficient, user-friendly, and complementary solution for large-scale personalized constraint-based metabolic modeling.
  • The toolbox enhances the capabilities of COBRA 3.0, facilitating complex analyses.
  • FastMM is freely available under the GPL license, promoting wider adoption in research.