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

Amino Acid Biosynthetic Pathways01:29

Amino Acid Biosynthetic Pathways

1.2K
Amino acid biosynthesis is essential for cell growth, protein synthesis, and metabolic regulation. Cells generate essential and non-essential amino acids from metabolic intermediates to sustain vital biological functions. These intermediates originate from key metabolic pathways: glycolysis, the tricarboxylic acid (TCA) cycle, and the pentose phosphate pathway. Important precursors include α-ketoglutarate, pyruvate, oxaloacetate, phosphoenolpyruvate, and erythrose-4-phosphate, which...
1.2K
What is Metabolism?00:52

What is Metabolism?

132.0K
Overview
132.0K
C4 Pathway and CAM01:27

C4 Pathway and CAM

49.2K
Most plants use the C3 pathway for carbon fixation. However, some plants, such as sugar cane, corn, and cacti that grow in hot conditions, use alternative pathways to fix carbon and conserve energy loss due to photorespiration. Photorespiration is the process that occurs when the oxygen concentration is high. Under such conditions, the rubisco enzyme in the Calvin cycle binds O2 instead of CO2, which halts photosynthesis and consumes energy.
C4 Pathway
The C4 pathway is used by plants such as...
49.2K
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K

You might also read

Related Articles

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

Sort by
Same author

Deciphering global patterns of marine microbial community assembly and network stability.

mSystems·2026
Same author

UNified FramewOrk for reguLatory Dynamics (UNFOLD): Dissecting robustness, plasticity, evolvability and canalisation of biological function.

PLoS computational biology·2026
Same author

Unlocking the Metagenome: Pipeline for Microbiome Data Analysis.

Methods in molecular biology (Clifton, N.J.)·2026
Same author

Unveiling hidden microbial diversity in Mars 2020 mission assembly cleanrooms with molecular insights into the persistence and perseverance of novel species defying metagenome sequencing.

Microbiology spectrum·2026
Same author

Plasmidome, resistome, and virulence-associated gene characterization of <i>Acinetobacter johnsonii</i> in NASA cleanrooms and a clinical setting.

Microbiology spectrum·2026
Same author

Harnessing machine learning for metagenomic data analysis: trends and applications.

mSystems·2025

Related Experiment Video

Updated: Feb 8, 2026

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

25.0K

Enumerating all possible biosynthetic pathways in metabolic networks.

Aarthi Ravikrishnan1,2,3, Meghana Nasre4, Karthik Raman5,6,7

  • 1Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT), IIT Madras, Chennai, 600036, Tamil Nadu, India.

Scientific Reports
|July 4, 2018
PubMed
Summary

MetQuest efficiently finds all metabolic pathways in complex networks. This graph-theoretic algorithm aids in understanding cellular metabolism and microbial interactions.

More Related Videos

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

3.8K
Author Spotlight: Tackling Challenges in Synthetic Cell Engineering
10:56

Author Spotlight: Tackling Challenges in Synthetic Cell Engineering

Published on: April 12, 2024

1.7K

Related Experiment Videos

Last Updated: Feb 8, 2026

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

25.0K
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

3.8K
Author Spotlight: Tackling Challenges in Synthetic Cell Engineering
10:56

Author Spotlight: Tackling Challenges in Synthetic Cell Engineering

Published on: April 12, 2024

1.7K

Area of Science:

  • Metabolic Engineering
  • Computational Biology
  • Systems Biology

Background:

  • Metabolic networks are crucial for understanding cellular functions.
  • Existing pathway enumeration methods struggle with scalability for large networks like microbial communities.
  • Efficiently identifying alternate metabolic pathways is essential for biological insights.

Purpose of the Study:

  • To develop an efficient and scalable algorithm for enumerating all possible metabolic pathways.
  • To provide a tool for analyzing metabolic reconstructions, including those of microbial communities.
  • To facilitate the discovery of novel metabolic pathways and interactions.

Main Methods:

  • Developed MetQuest, a graph-theoretic algorithm utilizing guided breadth-first search.
  • Employed dynamic programming for novel pathway enumeration based on precursor availability.
  • Algorithm enumerates pathways of a specific size between source and target molecules.

Main Results:

  • Demonstrated MetQuest's efficiency and scalability on large metabolic network graphs.
  • Successfully identified amino acid biosynthesis pathways and diverse degradation pathways.
  • Revealed metabolic interactions within microbial communities.

Conclusions:

  • MetQuest offers an efficient solution for comprehensive metabolic pathway enumeration.
  • The algorithm scales effectively for large-scale biological network analysis.
  • MetQuest provides valuable insights into cellular metabolism and microbial community interactions.