Modeling protein structure alignment based on Markov random field theory

The availability of three-dimensional spatial information about protein structures is expanding, as a result of the increased use of both x-ray crystallography and nuclear magnetic resonance spectroscopy for structure elucidation. Frequently, a newly determined structure is similar in fold to a know...

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Main Author: Sheng, Xin.
Other Authors: Stan Z. Li
Format: Theses and Dissertations
Language:English
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/13207
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-132072023-07-04T15:30:43Z Modeling protein structure alignment based on Markov random field theory Sheng, Xin. Stan Z. Li School of Electrical and Electronic Engineering DRNTU::Engineering::Bioengineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems The availability of three-dimensional spatial information about protein structures is expanding, as a result of the increased use of both x-ray crystallography and nuclear magnetic resonance spectroscopy for structure elucidation. Frequently, a newly determined structure is similar in fold to a known one, even when no sequence similarity is detectable. Therefore the importance of protein structure alignment parallels that of sequence alignment. Protein structure alignment is to detect the optimal substructure equivalence between two given three-dimensional protein structures. Comparison of three-dimensional protein structures may reveal common arrangement of secondary structures which provides clues to functional relationships between proteins. The location of particularly stable substructures may be highlighted and therefore leads to a better understanding of the principle of protein folding. Master of Engineering 2008-08-05T04:39:07Z 2008-10-20T07:19:01Z 2008-08-05T04:39:07Z 2008-10-20T07:19:01Z 1999 1999 Thesis http://hdl.handle.net/10356/13207 en 112 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Bioengineering
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Bioengineering
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Sheng, Xin.
Modeling protein structure alignment based on Markov random field theory
description The availability of three-dimensional spatial information about protein structures is expanding, as a result of the increased use of both x-ray crystallography and nuclear magnetic resonance spectroscopy for structure elucidation. Frequently, a newly determined structure is similar in fold to a known one, even when no sequence similarity is detectable. Therefore the importance of protein structure alignment parallels that of sequence alignment. Protein structure alignment is to detect the optimal substructure equivalence between two given three-dimensional protein structures. Comparison of three-dimensional protein structures may reveal common arrangement of secondary structures which provides clues to functional relationships between proteins. The location of particularly stable substructures may be highlighted and therefore leads to a better understanding of the principle of protein folding.
author2 Stan Z. Li
author_facet Stan Z. Li
Sheng, Xin.
format Theses and Dissertations
author Sheng, Xin.
author_sort Sheng, Xin.
title Modeling protein structure alignment based on Markov random field theory
title_short Modeling protein structure alignment based on Markov random field theory
title_full Modeling protein structure alignment based on Markov random field theory
title_fullStr Modeling protein structure alignment based on Markov random field theory
title_full_unstemmed Modeling protein structure alignment based on Markov random field theory
title_sort modeling protein structure alignment based on markov random field theory
publishDate 2008
url http://hdl.handle.net/10356/13207
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