Biomod/2011/PSU/BlueGenes/method: Difference between revisions
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Gaussian Network Model (GNM) predicts the flexibility of the structure by reducing it to be a set of certain atoms. The interactions of these atoms depend solely on their location. This representative set of atoms is known as nodes. Then a cutoff distance is defined such that outside of this distance, there are no interactions between nodes. | Gaussian Network Model (GNM) predicts the flexibility of the structure by reducing it to be a set of certain atoms. The interactions of these atoms depend solely on their location. This representative set of atoms is known as nodes. Then a cutoff distance is defined such that outside of this distance, there are no interactions between nodes. | ||
[[Image:Nodes.png|Image from http://ignm.ccbb.pitt.edu/GNM_Online_Calculation.htm]] | |||
For a network of N nodes with given coordinates, the cutoff distnace is r<sub>c</sub>. The fundamental NxN Kirchhoff matrix, Γ, has elements: | |||
[[Image:Kirchoff.png]] | |||
where r<sub>ij</sub> is the distance between node i and node j. H(x) is the Heaviside step function where H(x)=1 for x>0 and H(x)=0 for x≤0. | |||
Revision as of 12:21, 18 October 2011
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Home ::: Overview ::: Methods ::: Results ::: Application ::: Literature ::: Team |
GNMGaussian Network Model (GNM) predicts the flexibility of the structure by reducing it to be a set of certain atoms. The interactions of these atoms depend solely on their location. This representative set of atoms is known as nodes. Then a cutoff distance is defined such that outside of this distance, there are no interactions between nodes.
For a network of N nodes with given coordinates, the cutoff distnace is rc. The fundamental NxN Kirchhoff matrix, Γ, has elements:
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