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

Overview of Metabolism01:40

Overview of Metabolism

37.4K
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...
37.4K
Export of Mitochondrial and Chloroplast Genes02:19

Export of Mitochondrial and Chloroplast Genes

4.1K
A eukaryotic cell can have up to three different types of genetic systems: nuclear, mitochondrial, and chloroplast. During evolution, organelles have exported many genes to the nucleus; this transfer is still ongoing in some plant species. Approximately 18% of the Arabidopsis thaliana nuclear genome is thought to be derived from the chloroplast’s cyanobacterial ancestor, and around 75% of the yeast genome derived from the mitochondria’s bacterial ancestor. This export has occurred...
4.1K
Metabolism of Chemolithotrophs01:15

Metabolism of Chemolithotrophs

658
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.
658
Synthetic Biology02:55

Synthetic Biology

5.4K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
5.4K
Overview of Protein Metabolism01:21

Overview of Protein Metabolism

3.4K
Proteins are broken down into amino acids during digestion. Unlike fats and carbohydrates, which are stored for later use, proteins are not. Instead, amino acids are either used to produce ATP through oxidation or contribute to the creation of new proteins for the growth and repair of the body. Any surplus amino acids from the diet are converted into glucose or triglycerides rather than excreted.
Amino acids play various roles in the body once they are absorbed into cells. They are restructured...
3.4K
Introduction to Metabolism01:30

Introduction to Metabolism

2.5K
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...
2.5K

You might also read

Related Articles

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

Sort by
Same author

ZW4864-mediated inhibition of the β-catenin/BCL9/BCL9L complex reveals therapeutic potential in bladder cancer.

Molecular oncology·2026
Same author

Predictive factors for poor mobilization in autologous stem cell transplant: a multivariate model.

Hematology, transfusion and cell therapy·2026
Same author

Quercetin-loaded cellulose nanofibers improve memory, learning, and attenuate endoplasmic reticulum stress in a rat model of Alzheimer's disease.

Scientific reports·2026
Same author

The PEGS DREAM Challenge: A Crowdsourcing Approach to Understanding Hypercholesterolemia with Multi- dimensional Genomic and Environmental Data.

Research square·2026
Same author

Intertwining of the IGF system and animal welfare.

Scientific reports·2026
Same author

Enhancing node influence prediction in large networks via multi-Level knowledge distillation.

Neural networks : the official journal of the International Neural Network Society·2025

Related Experiment Video

Updated: Dec 29, 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

GEMtractor: extracting views into genome-scale metabolic models.

Martin Scharm1, Olaf Wolkenhauer1,2, Mahdi Jalili3

  • 1Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany.

Bioinformatics (Oxford, England)
|February 1, 2020
PubMed
Summary

The GEMtractor tool simplifies the comparison of genome-scale metabolic models (GEMs) by extracting relevant subnetworks. This web-based utility focuses on reaction- and enzyme-centric views, making complex network analysis more manageable.

More Related Videos

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry
08:06

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry

Published on: October 25, 2019

9.6K
Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

9.0K

Related Experiment Videos

Last Updated: Dec 29, 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
Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry
08:06

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry

Published on: October 25, 2019

9.6K
Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

9.0K

Area of Science:

  • Systems Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-scale metabolic models (GEMs) are complex graph representations of cellular metabolism.
  • Comparing large-scale models using topological analysis is computationally challenging.
  • Full network comparison is often unnecessary for specific biological questions.

Purpose of the Study:

  • To develop a user-friendly web tool for simplifying the analysis of metabolic models.
  • To enable efficient extraction of relevant subnetworks from larger models.
  • To facilitate reaction- and enzyme-centric views for focused biological insights.

Main Methods:

  • Implementation of a web-based tool named GEMtractor.
  • Utilizing SBML (Systems Biology Markup Language) file format for model input.
  • Development of algorithms for subnetwork extraction based on user-defined criteria.

Main Results:

  • GEMtractor provides a streamlined approach to trim complex metabolic models.
  • The tool allows for the generation of focused, smaller networks for analysis.
  • Enables easier visualization and study of specific metabolic pathways or enzyme functions.

Conclusions:

  • GEMtractor offers a practical solution for navigating and analyzing large metabolic models.
  • The tool enhances the accessibility of comparative analyses of genome-scale models.
  • Facilitates deeper understanding of specific metabolic components through subnetwork extraction.