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

Operon Model01:23

Operon Model

The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...
Metabolism of Chemolithotrophs01:15

Metabolism of Chemolithotrophs

Chemolithotrophs are microorganisms that obtain energy by oxidizing inorganic molecules such as hydrogen gas (H₂), ammonia (NH₃), reduced sulfur compounds (H₂S, S²⁻), and ferrous iron (Fe²⁺). Unlike heterotrophic organisms that rely on organic carbon, chemolithotrophs transfer electrons from these inorganic donors to the electron transport chain (ETC), generating a proton motive force (PMF) that drives ATP synthesis through oxidative phosphorylation. However, because inorganic electron donors...
Regulation of Metabolism01:19

Regulation of Metabolism

Cellular needs and conditions vary from cell to cell and change within individual cells over time. For example, the required enzymes and energetic demands of stomach cells are different from those of fat storage cells, skin cells, blood cells, and nerve cells. Furthermore, a digestive cell works much harder to process and break down nutrients during the time that closely follows a meal compared with many hours after a meal. As these cellular demands and conditions vary, so do the amounts and...
Introduction to Metabolism01:30

Introduction to Metabolism

Metabolism encompasses all biochemical reactions in a living organism, facilitating both the breakdown and synthesis of biomolecules. These metabolic processes are categorized into catabolic and anabolic pathways, which operate in a coordinated manner to ensure energy balance and cellular function.Catabolic Pathways and Energy ReleaseCatabolic pathways involve the breakdown of complex macromolecules such as carbohydrates, lipids, and proteins into smaller structures like monosaccharides, fatty...
Overview of Metabolism01:40

Overview of Metabolism

Living cells constantly carry out various chemical reactions which are necessary for their proper functioning. These reactions are interlinked to one another via multiple pathways. The collection of these chemical reactions is known as metabolism.
Plant Metabolism
Sunlight, the primary source of energy in plants, is first absorbed by the chlorophyll pigments present in their leaves. Plants then use this energy to carry out photosynthesis, where water is oxidized into oxygen and carbon dioxide...
What is Metabolism?00:52

What is Metabolism?

Overview

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

Another 10 years of PLOS Computational Biology: A data-driven reflection on trends in genomics research.

PLoS computational biology·2026
Same journal

Mobility data resolution needed to inform predictive models of spatial epidemic spread from mobile phone data.

PLoS computational biology·2026
Same journal

DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.

PLoS computational biology·2026
Same journal

Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.

PLoS computational biology·2026
Same journal

Optimized phenotype definitions boost GWAS power.

PLoS computational biology·2026
Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026
See all related articles

Related Experiment Video

Updated: Jul 5, 2026

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources
12:47

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Published on: January 22, 2018

Context-specific metabolic networks are consistent with experiments.

Scott A Becker1, Bernhard O Palsson

  • 1Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.

Plos Computational Biology
|May 17, 2008
PubMed
Summary
This summary is machine-generated.

We developed Gene Inactivity Moderated by Metabolism and Expression (GIMME) to create context-specific metabolic models. This method uses gene expression data to tailor genome-scale reconstructions for accurate in silico predictions.

More Related Videos

Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids
07:26

Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids

Published on: January 26, 2012

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging
11:43

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging

Published on: December 30, 2016

Related Experiment Videos

Last Updated: Jul 5, 2026

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources
12:47

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Published on: January 22, 2018

Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids
07:26

Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids

Published on: January 26, 2012

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging
11:43

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging

Published on: December 30, 2016

Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Computational Biology

Background:

  • Genome-scale metabolic reconstructions are comprehensive but not condition-specific.
  • Tailoring these networks is crucial for accurate in silico modeling under specific conditions.

Purpose of the Study:

  • To present a computational method for generating context-specific metabolic models.
  • To enable more accurate predictive modeling by integrating gene expression data.

Main Methods:

  • Developed the Gene Inactivity Moderated by Metabolism and Expression (GIMME) algorithm.
  • GIMME utilizes quantitative gene expression data and metabolic objectives.
  • The algorithm produces context-specific reconstructions and an inconsistency score.

Main Results:

  • GIMME successfully generated context-specific metabolic models.
  • Results align with biological experiments in bacteria and human cells.
  • Demonstrated utility in adaptive evolution and metabolic engineering.

Conclusions:

  • GIMME advances the creation of constraint-based metabolic models.
  • This method allows for condition-specific models where expression data is available.
  • Facilitates more precise in silico analysis of cellular metabolism.