By the same authors

The use of wavelet transforms in low-resolution phase extension

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

The use of wavelet transforms in low-resolution phase extension. / Wilson, J; Main, P.

METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY. ed. / D Turk; L Johnson. AMSTERDAM : I O S PRESS, 2001. p. 82-94.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Wilson, J & Main, P 2001, The use of wavelet transforms in low-resolution phase extension. in D Turk & L Johnson (eds), METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY. I O S PRESS, AMSTERDAM, pp. 82-94, Conference of the NATO-Advanced-Study-Institutes on Methods in Macromolecular Crystallography and Chemical Prospectives in Crystallography of Molecular Biology, ERICE, 25/05/00.

APA

Wilson, J., & Main, P. (2001). The use of wavelet transforms in low-resolution phase extension. In D. Turk, & L. Johnson (Eds.), METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY (pp. 82-94). AMSTERDAM: I O S PRESS.

Vancouver

Wilson J, Main P. The use of wavelet transforms in low-resolution phase extension. In Turk D, Johnson L, editors, METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY. AMSTERDAM: I O S PRESS. 2001. p. 82-94

Author

Wilson, J ; Main, P. / The use of wavelet transforms in low-resolution phase extension. METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY. editor / D Turk ; L Johnson. AMSTERDAM : I O S PRESS, 2001. pp. 82-94

Bibtex - Download

@inproceedings{26515f4d98cd44458cce79dfe2e49f4e,
title = "The use of wavelet transforms in low-resolution phase extension",
abstract = "A method to extend low-resolution phases has been developed using histogram- matching, not only of the electron density, but also of histograms obtained from the different levels of detail in the electron density provided by its wavelet transform. Like Fourier analysis, wavelet analysis can be used to express an image (the electron density) in terms of a set of orthogonal functions. Unlike Fourier analysis though, the wavelet functions are localized in position as well as frequency. The wavelet transform of an image therefore provides a set of wavelet coefficients, each one giving the size of the contribution of the corresponding wavelet function to a particular position in the image. Using mathematical models to describe the different histograms we are able to predict the coefficients for an increased resolution and the inverse transform allows a new image to be reconstructed from these wavelet coefficients. The procedure alternates between real and reciprocal space so that the positions of new features in the map are also guided by the diffraction pattern. The method has been tried on a large number of model structures varying in size, solvent content and space-group. There is a build-up of errors as the calculation proceeds, but, starting with a good 10 Angstrom map, we are currently able to produce new phases to about 6-7 Angstrom with reasonable phase errors on all the structures tested. In most cases, the 10 Angstrom map is little more than a mask roughly covering the molecule, whereas in the maps we obtain, secondary structure can often be identified. It is hoped that the addition of further information, such as knowledge of secondary structure, will improve the method and eventually allow phase extension to a resolution at which existing density modification techniques are effective.",
keywords = "ELECTRON-DENSITY HISTOGRAMS, REAL",
author = "J Wilson and P Main",
year = "2001",
language = "English",
isbn = "1-58603-080-9",
pages = "82--94",
editor = "D Turk and L Johnson",
booktitle = "METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY",
publisher = "I O S PRESS",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - The use of wavelet transforms in low-resolution phase extension

AU - Wilson, J

AU - Main, P

PY - 2001

Y1 - 2001

N2 - A method to extend low-resolution phases has been developed using histogram- matching, not only of the electron density, but also of histograms obtained from the different levels of detail in the electron density provided by its wavelet transform. Like Fourier analysis, wavelet analysis can be used to express an image (the electron density) in terms of a set of orthogonal functions. Unlike Fourier analysis though, the wavelet functions are localized in position as well as frequency. The wavelet transform of an image therefore provides a set of wavelet coefficients, each one giving the size of the contribution of the corresponding wavelet function to a particular position in the image. Using mathematical models to describe the different histograms we are able to predict the coefficients for an increased resolution and the inverse transform allows a new image to be reconstructed from these wavelet coefficients. The procedure alternates between real and reciprocal space so that the positions of new features in the map are also guided by the diffraction pattern. The method has been tried on a large number of model structures varying in size, solvent content and space-group. There is a build-up of errors as the calculation proceeds, but, starting with a good 10 Angstrom map, we are currently able to produce new phases to about 6-7 Angstrom with reasonable phase errors on all the structures tested. In most cases, the 10 Angstrom map is little more than a mask roughly covering the molecule, whereas in the maps we obtain, secondary structure can often be identified. It is hoped that the addition of further information, such as knowledge of secondary structure, will improve the method and eventually allow phase extension to a resolution at which existing density modification techniques are effective.

AB - A method to extend low-resolution phases has been developed using histogram- matching, not only of the electron density, but also of histograms obtained from the different levels of detail in the electron density provided by its wavelet transform. Like Fourier analysis, wavelet analysis can be used to express an image (the electron density) in terms of a set of orthogonal functions. Unlike Fourier analysis though, the wavelet functions are localized in position as well as frequency. The wavelet transform of an image therefore provides a set of wavelet coefficients, each one giving the size of the contribution of the corresponding wavelet function to a particular position in the image. Using mathematical models to describe the different histograms we are able to predict the coefficients for an increased resolution and the inverse transform allows a new image to be reconstructed from these wavelet coefficients. The procedure alternates between real and reciprocal space so that the positions of new features in the map are also guided by the diffraction pattern. The method has been tried on a large number of model structures varying in size, solvent content and space-group. There is a build-up of errors as the calculation proceeds, but, starting with a good 10 Angstrom map, we are currently able to produce new phases to about 6-7 Angstrom with reasonable phase errors on all the structures tested. In most cases, the 10 Angstrom map is little more than a mask roughly covering the molecule, whereas in the maps we obtain, secondary structure can often be identified. It is hoped that the addition of further information, such as knowledge of secondary structure, will improve the method and eventually allow phase extension to a resolution at which existing density modification techniques are effective.

KW - ELECTRON-DENSITY HISTOGRAMS

KW - REAL

M3 - Conference contribution

SN - 1-58603-080-9

SP - 82

EP - 94

BT - METHODS IN MACROMOLECULAR CRYSTALLOGRAPHY

A2 - Turk, D

A2 - Johnson, L

PB - I O S PRESS

CY - AMSTERDAM

ER -