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Related Concept Videos

Calculation of Electric Flux01:25

Calculation of Electric Flux

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?
Fermi Level Dynamics01:12

Fermi Level Dynamics

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.
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Understanding the movement of air masses is fundamental to meteorological analysis and atmospheric modeling. A key component in this process is quantifying the total mass of air that flows into or out of a defined region over a specified period of time. This is achieved by evaluating the mass flux across a boundary surface, a conceptual tool that simplifies the complex dynamics of atmospheric systems.To begin, an imaginary boundary surface S is introduced, enclosing the region of interest. The...
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Related Experiment Video

Updated: Jul 3, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

Large-scale computation of elementary flux modes with bit pattern trees.

Marco Terzer1, Jörg Stelling

  • 1Institute of Computational Science and Swiss Institute of Bioinformatics, ETH Zurich, 8092 Zurich, Switzerland.

Bioinformatics (Oxford, England)
|August 5, 2008
PubMed
Summary

New algorithms enable large-scale computation of elementary flux modes (EFMs) for metabolic networks. This breakthrough allows for deeper insights into cellular metabolism and pathway analysis, overcoming previous computational limitations.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Metabolic Network Analysis

Background:

  • Elementary flux modes (EFMs) are essential for steady-state metabolic network analysis.
  • Current EFM computation methods face scalability issues, hindering large-scale analyses.
  • EFM computation is equivalent to enumerating extreme rays of polyhedral cones.

Purpose of the Study:

  • To develop novel algorithms for large-scale elementary flux mode computation.
  • To overcome the limitations of existing combinatorial algorithms for EFM enumeration.
  • To enable comprehensive analysis of complex metabolic networks.

Main Methods:

  • Introduced new algorithmic concepts for large-scale EFM computation.
  • Developed a recursive enumeration strategy using bit pattern trees for adjacent rays.
  • Implemented rank updating and residue arithmetic methods for numerical stability and parallel computation.
  • Leveraged multi-core CPU architectures for performance enhancement.

Main Results:

  • Achieved an order of magnitude speedup compared to previous EFM computation methods.
  • Successfully computed ~26 million EFMs for the *Escherichia coli* central metabolism network.
  • Identified that the top 2% of modes significantly contribute to flux variability for biomass production.
  • Computed ~5 million EFMs for *Helicobacter pylori* genome-scale metabolic network, revealing >85% of modes for simultaneous amino acid production.

Conclusions:

  • The new algorithms enable unprecedented large-scale EFM analysis.
  • This facilitates deeper understanding of metabolic capabilities and pathway optimization.
  • The methods are crucial for analyzing complex biological systems and discovering novel metabolic functions.