Visualization of Protein Structure Relationships Using Twin Kernel Embedding

Yi Guo; Junbin Gao; Paul Hing Kwan; Kevin Hou

doi:10.1109/ICBBE.2007.4

Visualization of Protein Structure Relationships Using Twin Kernel Embedding

Yi Guo, Junbin Gao, Paul Hing Kwan, Kevin Hou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, a recently proposed dimensionality reduction method called twin kernel embedding (TKE) is applied in 2-dimensional visualization of protein structure relationships. By matching the similarity measures of the input and the embedding spaces expressed by their respective kernels, TKE ensures that both local and global proximity information are preserved simultaneously. Experiments conducted on a subset of the structural classification of protein (SCOP) database confirmed the effectiveness of TKE in preserving the original relationships among protein structures in the lower dimensional embedding according to their similarities. This result is expected to benefit subsequent analyses of protein structures and their functions.

Original language	English
Title of host publication	Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007)
Editors	IEEE: Institute of Electrical, Electronics Engineers
Place of Publication	Los Alamitos, United States of America
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-4
ISBN (Print)	1424411203
DOIs	https://doi.org/10.1109/ICBBE.2007.4
Publication status	Published - 2007
Event	ICBBE 2007: First International Conference on Bioinformatics and Biomedical Engineering - Wuhan, China Duration: 6 Jul 2007 → 8 Jul 2007

Conference

Conference	ICBBE 2007: First International Conference on Bioinformatics and Biomedical Engineering
City	Wuhan, China
Period	6/07/07 → 8/07/07

Keywords

Pattern Recognition and Data Mining

Access to Document

10.1109/ICBBE.2007.4

https://hdl.handle.net/1959.11/4586

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Guo, Y., Gao, J., Kwan, P. H., & Hou, K. (2007). Visualization of Protein Structure Relationships Using Twin Kernel Embedding. In IEEE. Institute of Electrical, & E. Engineers (Eds.), Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007) (pp. 1-4). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICBBE.2007.4

Guo, Yi ; Gao, Junbin ; Kwan, Paul Hing et al. / Visualization of Protein Structure Relationships Using Twin Kernel Embedding. Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007). editor / IEEE: Institute of Electrical ; Electronics Engineers. Los Alamitos, United States of America : Institute of Electrical and Electronics Engineers (IEEE), 2007. pp. 1-4

@inproceedings{b45dffa4e2c34c8d8f33379f1b6dabd8,

title = "Visualization of Protein Structure Relationships Using Twin Kernel Embedding",

abstract = "In this paper, a recently proposed dimensionality reduction method called twin kernel embedding (TKE) is applied in 2-dimensional visualization of protein structure relationships. By matching the similarity measures of the input and the embedding spaces expressed by their respective kernels, TKE ensures that both local and global proximity information are preserved simultaneously. Experiments conducted on a subset of the structural classification of protein (SCOP) database confirmed the effectiveness of TKE in preserving the original relationships among protein structures in the lower dimensional embedding according to their similarities. This result is expected to benefit subsequent analyses of protein structures and their functions.",

keywords = "Pattern Recognition and Data Mining",

author = "Yi Guo and Junbin Gao and Kwan, \{Paul Hing\} and Kevin Hou",

year = "2007",

doi = "10.1109/ICBBE.2007.4",

language = "English",

isbn = "1424411203",

pages = "1--4",

editor = "\{Institute of Electrical\}, IEEE: and Electronics Engineers",

booktitle = "Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

note = "ICBBE 2007: First International Conference on Bioinformatics and Biomedical Engineering ; Conference date: 06-07-2007 Through 08-07-2007",

}

Guo, Y, Gao, J, Kwan, PH & Hou, K 2007, Visualization of Protein Structure Relationships Using Twin Kernel Embedding. in IEEE Institute of Electrical & E Engineers (eds), Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007). Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, United States of America, pp. 1-4, ICBBE 2007: First International Conference on Bioinformatics and Biomedical Engineering, Wuhan, China, 6/07/07. https://doi.org/10.1109/ICBBE.2007.4

Visualization of Protein Structure Relationships Using Twin Kernel Embedding. / Guo, Yi; Gao, Junbin; Kwan, Paul Hing et al.
Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007). ed. / IEEE: Institute of Electrical; Electronics Engineers. Los Alamitos, United States of America: Institute of Electrical and Electronics Engineers (IEEE), 2007. p. 1-4.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Visualization of Protein Structure Relationships Using Twin Kernel Embedding

AU - Guo, Yi

AU - Gao, Junbin

AU - Kwan, Paul Hing

AU - Hou, Kevin

PY - 2007

Y1 - 2007

N2 - In this paper, a recently proposed dimensionality reduction method called twin kernel embedding (TKE) is applied in 2-dimensional visualization of protein structure relationships. By matching the similarity measures of the input and the embedding spaces expressed by their respective kernels, TKE ensures that both local and global proximity information are preserved simultaneously. Experiments conducted on a subset of the structural classification of protein (SCOP) database confirmed the effectiveness of TKE in preserving the original relationships among protein structures in the lower dimensional embedding according to their similarities. This result is expected to benefit subsequent analyses of protein structures and their functions.

AB - In this paper, a recently proposed dimensionality reduction method called twin kernel embedding (TKE) is applied in 2-dimensional visualization of protein structure relationships. By matching the similarity measures of the input and the embedding spaces expressed by their respective kernels, TKE ensures that both local and global proximity information are preserved simultaneously. Experiments conducted on a subset of the structural classification of protein (SCOP) database confirmed the effectiveness of TKE in preserving the original relationships among protein structures in the lower dimensional embedding according to their similarities. This result is expected to benefit subsequent analyses of protein structures and their functions.

KW - Pattern Recognition and Data Mining

UR - http://trove.nla.gov.au/work/35178324

UR - https://www.scopus.com/pages/publications/35348917296

U2 - 10.1109/ICBBE.2007.4

DO - 10.1109/ICBBE.2007.4

M3 - Conference contribution

SN - 1424411203

SP - 1

EP - 4

BT - Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007)

A2 - Institute of Electrical, IEEE:

A2 - Engineers, Electronics

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Los Alamitos, United States of America

T2 - ICBBE 2007: First International Conference on Bioinformatics and Biomedical Engineering

Y2 - 6 July 2007 through 8 July 2007

ER -

Guo Y, Gao J, Kwan PH, Hou K. Visualization of Protein Structure Relationships Using Twin Kernel Embedding. In Institute of Electrical IEEE, Engineers E, editors, Proceedings of the First International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2007). Los Alamitos, United States of America: Institute of Electrical and Electronics Engineers (IEEE). 2007. p. 1-4 doi: 10.1109/ICBBE.2007.4

Visualization of Protein Structure Relationships Using Twin Kernel Embedding

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