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

Calculation of Electric Flux01:25

Calculation of Electric Flux

3.5K
Consider the electric field of an oppositely charged, parallel-plate system and an imaginary box between those plates. Let the bottom face of the box be ABCD, and the top face be FGHK. The electric field between the plates is uniform and points from the positive plate toward the negative plate. The calculation of this field's flux through the box's various faces shows that the net flux through the box is zero. Why does the flux cancel out here?
3.5K
Methods of Medium Optimization01:28

Methods of Medium Optimization

63
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
63
Design Example: Traverse Angle Computations01:25

Design Example: Traverse Angle Computations

443
Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
443
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

929
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
929
Fermi Level Dynamics01:12

Fermi Level Dynamics

1.1K
The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
1.1K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

416
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
416

You might also read

Related Articles

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

Sort by
Same author

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

Blood·2026
Same author

gMISpy: integration of complex regulatory networks and genome scale metabolic models.

Bioinformatics (Oxford, England)·2026
Same author

Treatment monitoring by biomarker analysis in a Phase I dose-expansion study of AZD2811 for relapsed/refractory small-cell lung cancer.

British journal of cancer·2026
Same author

Obtaining PDC and other high-added value products from lignin by <i>in silico</i> genetic engineering in <i>Novosphingobium aromaticivorans</i>.

Journal of integrative bioinformatics·2026
Same author

Beyond synthetic lethality in large-scale metabolic and regulatory network models via genetic minimal intervention set.

Bioinformatics advances·2026
Same author

Early ctDNA Dynamics Inform First-Line Therapy in Patients with Extensive-Stage Small Cell Lung Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research·2025
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Apr 21, 2026

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.6K

TreeEFM: calculating elementary flux modes using linear optimization in a tree-based algorithm.

Jon Pey1, Juan A Villar1, Luis Tobalina1

  • 1CEIT and TECNUN, University of Navarra, Manuel de Lardizabal 15, 20018 San Sebastian, Spain, Computer Engineering Department, School of Computer Science, POB 30100 University of Murcia, Spain and Mathematical Sciences, Brunel University, Kingston Lane, UB8 3PH Uxbridge, UK.

Bioinformatics (Oxford, England)
|November 9, 2014
PubMed
Summary
This summary is machine-generated.

A new algorithm efficiently calculates elementary flux modes (EFMs) in genome-scale metabolic networks (GSMNs), significantly outperforming existing methods and aiding in metabolic pathway analysis.

More Related Videos

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

4.1K

Related Experiment Videos

Last Updated: Apr 21, 2026

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.6K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

4.1K

Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Computational Biology

Background:

  • Elementary flux modes (EFMs) are crucial for analyzing metabolic networks.
  • Efficiently calculating EFMs in genome-scale metabolic networks (GSMNs) remains a significant computational challenge.

Purpose of the Study:

  • To present a novel, efficient algorithm for enumerating a subset of EFMs in GSMNs.
  • To demonstrate the computational advantage of the new algorithm over existing methods.
  • To validate the algorithm's utility in analyzing complex metabolic phenomena like acetate overflow.

Main Methods:

  • A linear programming-based tree search algorithm is employed.
  • The algorithm is implemented in C++ and utilizes the COIN-OR CLP solver.
  • The approach was tested on genome-scale metabolic networks, including analysis of Escherichia coli metabolism.

Main Results:

  • The novel algorithm shows significant improvements in computation time compared to the EFMEvolver approach.
  • Analysis of acetate overflow metabolism in E. coli using 1 million EFMs showed good agreement with experimental data.
  • The algorithm's performance was evaluated on large-scale GSMNs, demonstrating scalability.

Conclusions:

  • The developed algorithm provides a more efficient method for EFM enumeration in GSMNs.
  • This approach facilitates deeper insights into cellular metabolism and pathway relevance.
  • The tool aids in understanding complex metabolic behaviors and validating experimental findings.