Effective moment feature vectors for protein domain structures.

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing...

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Autores principales:	Jian-Yu Shi, Siu-Ming Yiu, Yan-Ning Zhang, Francis Yuk-Lun Chin
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/810c6f923bb846abbf479ae7d7f1fba5
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id	oai:doaj.org-article:810c6f923bb846abbf479ae7d7f1fba5
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spelling	oai:doaj.org-article:810c6f923bb846abbf479ae7d7f1fba52021-11-18T08:39:31ZEffective moment feature vectors for protein domain structures.1932-620310.1371/journal.pone.0083788https://doaj.org/article/810c6f923bb846abbf479ae7d7f1fba52013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24391828/?tool=EBIhttps://doaj.org/toc/1932-6203Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100-400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity.Jian-Yu ShiSiu-Ming YiuYan-Ning ZhangFrancis Yuk-Lun ChinPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 12, p e83788 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jian-Yu Shi Siu-Ming Yiu Yan-Ning Zhang Francis Yuk-Lun Chin Effective moment feature vectors for protein domain structures.
description	Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100-400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity.
format	article
author	Jian-Yu Shi Siu-Ming Yiu Yan-Ning Zhang Francis Yuk-Lun Chin
author_facet	Jian-Yu Shi Siu-Ming Yiu Yan-Ning Zhang Francis Yuk-Lun Chin
author_sort	Jian-Yu Shi
title	Effective moment feature vectors for protein domain structures.
title_short	Effective moment feature vectors for protein domain structures.
title_full	Effective moment feature vectors for protein domain structures.
title_fullStr	Effective moment feature vectors for protein domain structures.
title_full_unstemmed	Effective moment feature vectors for protein domain structures.
title_sort	effective moment feature vectors for protein domain structures.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/810c6f923bb846abbf479ae7d7f1fba5
work_keys_str_mv	AT jianyushi effectivemomentfeaturevectorsforproteindomainstructures AT siumingyiu effectivemomentfeaturevectorsforproteindomainstructures AT yanningzhang effectivemomentfeaturevectorsforproteindomainstructures AT francisyuklunchin effectivemomentfeaturevectorsforproteindomainstructures
_version_	1718421510394216448

Effective moment feature vectors for protein domain structures.

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