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Related Concept Videos

Quantitative Analysis01:12

Quantitative Analysis

1.4K
Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
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Electric Flux01:15

Electric Flux

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The concept of flux describes how much of something goes through a given area. More formally, it is the dot product of a vector field within an area. For a better understanding, consider an open rectangular surface with a small area that is placed in a uniform electric field. The larger the area, the more field lines go through it and, hence, the greater the flux; similarly, the stronger the electric field (represented by a greater density of lines), the greater the flux. On the other hand, if...
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Magnetic Flux01:18

Magnetic Flux

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The magnetic flux measures the number of magnetic field lines passing through a given surface area. The SI unit for magnetic flux is the weber (Wb). Magnetic flux is a scalar quantity. It depends on three factors: the strength of the magnetic field B, the area through which the field lines pass, and the relative orientation of the field with the surface area.
Suppose a surface is divided into elements of area dA. For each element, the component of the magnetic field that is normal to the...
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Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

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Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
The central atom need not be NMR-active because its electrons are affected by the electron polarization of the spin-active atoms. However, spin information is transmitted less effectively than in one-bond coupling, and 2J values are usually weaker than 1J values. The energy of...
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Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)

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Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the involved orbitals. The...
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G-protein Coupled Receptors01:21

G-protein Coupled Receptors

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G-protein coupled receptors are ligand binding receptors that indirectly affect changes in the cell. The actual receptor is a single polypeptide that transverses the cell membrane seven times creating intracellular and extracellular loops. The extracellular loops create a ligand specific pocket which binds to neurotransmitters or hormones. The intracellular loops holds onto the G-protein.
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Preparation of Washed Human Platelets for Quantitative Metabolic Flux Studies
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Quantitative flux coupling analysis.

Mojtaba Tefagh1, Stephen P Boyd2

  • 1Information Systems Laboratory, Department of Electrical Engineering, Stanford University, Stanford, CA, USA. mtefagh@stanford.edu.

Journal of Mathematical Biology
|December 12, 2018
PubMed
Summary
This summary is machine-generated.

Quantitative Flux Coupling Analysis (QFCA) provides numerical bounds for metabolic reaction dependencies, overcoming qualitative limitations of traditional Flux Coupling Analysis (FCA). This method quantifies coupling strengths and identifies underlying metabolic bottlenecks.

Keywords:
FCAFlux coupling analysisFlux coupling equationMetabolic network analysisQFCASystems biology

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Area of Science:

  • Systems Biology
  • Metabolic Network Analysis
  • Computational Biology

Background:

  • Flux Coupling Analysis (FCA) qualitatively describes functional dependencies between metabolic reactions.
  • Existing FCA methods lack quantitative bounds and insights into the causes of flux couplings.
  • Understanding these dependencies is crucial for metabolic engineering and systems biology.

Purpose of the Study:

  • To introduce Quantitative Flux Coupling Analysis (QFCA) for a numerically bounded description of metabolic reaction dependencies.
  • To develop an efficient algorithm for identifying quantitative flux coupling equations in large-scale metabolic networks.
  • To enable quantification of flux coupling strengths and identification of enforcing metabolites.

Main Methods:

  • Development of quantitative flux coupling equations.
  • Design of a scalable algorithm for identifying these equations in genome-scale metabolic networks.
  • Formulation of biologically meaningful interpretations, including metabolite-centric explanations.

Main Results:

  • QFCA generalizes qualitative FCA, providing all existing information plus quantitative insights.
  • The proposed algorithm efficiently identifies quantitative flux coupling equations for large networks.
  • QFCA quantifies coupling strengths and identifies specific metabolites responsible for flux dependencies.

Conclusions:

  • QFCA offers a powerful quantitative framework for analyzing metabolic network dependencies.
  • The method provides deeper insights into metabolic bottlenecks and functional relationships.
  • QFCA shows potential for applications in metabolic gap-filling and network reconstruction.