dccm.gnm: Dynamic Cross-Correlation from Gaussian Network Model

In bio3d: Biological Structure Analysis

Dynamic Cross-Correlation from Gaussian Network Model

Description

Calculate the cross-correlation matrix from Gaussian network model normal modes analysis.

Usage

## S3 method for class 'gnm'
dccm(x, ...)

## S3 method for class 'egnm'
dccm(x, ...)

Arguments

x	an object of class ‘gnm’ or ‘egnm’ as obtained from gnm.
...	additional arguments (currently ignored).

Details

This function calculates the cross-correlation matrix from Gaussian network model (GNM) normal modes analysis (NMA) obtained from gnm. It returns a matrix of residue-wise cross-correlations whose elements, Cij, may be displayed in a graphical representation frequently termed a dynamical cross-correlation map, or DCCM. (See more details in help(dccm.nma)).

Value

Returns a cross-correlation matrix.

Author(s)

Xin-Qiu Yao & Lars Skjaerven

References

Bahar, I. et al. (1997) Folding Des. 2, 173.

See Also

gnm, dccm.nma, dccm.enma, plot.dccm.

Examples

if(!requireNamespace("lattice", quietly=TRUE)) {
   message("Need lattice installed to run this example")
} else {

## Fetch stucture
pdb <- read.pdb( system.file("examples/1hel.pdb", package="bio3d") )
   
## Calculate normal modes
modes <- gnm(pdb)
   
## Calculate correlation matrix
cm <- dccm(modes)

## Plot correlation map
plot(cm, sse = pdb, contour = FALSE, col.regions = bwr.colors(20),
     at = seq(-1, 1, 0.1))

}

bio3d documentation built on Oct. 30, 2024, 1:08 a.m.