Protein fold recognition and remote homology detection based on profile-level building blocks

Lei Lin; Yi Shen; Bin Liu; Xiaolong Wang

doi:10.1109/ICBECS.2010.5462512

Protein fold recognition and remote homology detection based on profile-level building blocks

Lei Lin^*, Yi Shen, Bin Liu, Xiaolong Wang

^*Corresponding author for this work

Harbin Institute of Technology

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

2 Citations (Scopus)

Abstract

Protein remote homology detection and fold recognition are central problems in bioinformatics. In this paper, two kinds of profile-level building blocks of protein sequences, binary profiles and N-nary profiles, are presented, which contain the evolutionary information of the protein sequence frequency profile. The two building blocks are applied for protein remote homology and fold detection tasks. The latent semantic analysis (LSA) model is adopted to further improve the performance of our methods. Experiment results show that the methods based on profile-level building blocks give better results compared to related methods.

Original language	English
Title of host publication	2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010
DOIs	https://doi.org/10.1109/ICBECS.2010.5462512
Publication status	Published - 2010
Externally published	Yes
Event	2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 - Wuhan, China Duration: 23 Apr 2010 → 25 Apr 2010

Publication series

Name	2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

Conference

Conference	2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010
Country/Territory	China
City	Wuhan
Period	23/04/10 → 25/04/10

Keywords

Fold recognition
Latent semantic analysis
Remote homology detection
Support vector machine

Access to Document

10.1109/ICBECS.2010.5462512

Cite this

Lin, L., Shen, Y., Liu, B., & Wang, X. (2010). Protein fold recognition and remote homology detection based on profile-level building blocks. In 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 Article 5462512 (2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010). https://doi.org/10.1109/ICBECS.2010.5462512

@inproceedings{6bf52b21b02d4494bbe9b3f049e66b3f,

title = "Protein fold recognition and remote homology detection based on profile-level building blocks",

abstract = "Protein remote homology detection and fold recognition are central problems in bioinformatics. In this paper, two kinds of profile-level building blocks of protein sequences, binary profiles and N-nary profiles, are presented, which contain the evolutionary information of the protein sequence frequency profile. The two building blocks are applied for protein remote homology and fold detection tasks. The latent semantic analysis (LSA) model is adopted to further improve the performance of our methods. Experiment results show that the methods based on profile-level building blocks give better results compared to related methods.",

keywords = "Fold recognition, Latent semantic analysis, Remote homology detection, Support vector machine",

author = "Lei Lin and Yi Shen and Bin Liu and Xiaolong Wang",

year = "2010",

doi = "10.1109/ICBECS.2010.5462512",

language = "English",

isbn = "9781424453153",

series = "2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010",

booktitle = "2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010",

note = "2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 ; Conference date: 23-04-2010 Through 25-04-2010",

}

Lin, L, Shen, Y, Liu, B & Wang, X 2010, Protein fold recognition and remote homology detection based on profile-level building blocks. in 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010., 5462512, 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010, 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010, Wuhan, China, 23/04/10. https://doi.org/10.1109/ICBECS.2010.5462512

Protein fold recognition and remote homology detection based on profile-level building blocks. / Lin, Lei; Shen, Yi; Liu, Bin et al.
2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010. 2010. 5462512 (2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010).

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

TY - GEN

T1 - Protein fold recognition and remote homology detection based on profile-level building blocks

AU - Lin, Lei

AU - Shen, Yi

AU - Liu, Bin

AU - Wang, Xiaolong

PY - 2010

Y1 - 2010

N2 - Protein remote homology detection and fold recognition are central problems in bioinformatics. In this paper, two kinds of profile-level building blocks of protein sequences, binary profiles and N-nary profiles, are presented, which contain the evolutionary information of the protein sequence frequency profile. The two building blocks are applied for protein remote homology and fold detection tasks. The latent semantic analysis (LSA) model is adopted to further improve the performance of our methods. Experiment results show that the methods based on profile-level building blocks give better results compared to related methods.

AB - Protein remote homology detection and fold recognition are central problems in bioinformatics. In this paper, two kinds of profile-level building blocks of protein sequences, binary profiles and N-nary profiles, are presented, which contain the evolutionary information of the protein sequence frequency profile. The two building blocks are applied for protein remote homology and fold detection tasks. The latent semantic analysis (LSA) model is adopted to further improve the performance of our methods. Experiment results show that the methods based on profile-level building blocks give better results compared to related methods.

KW - Fold recognition

KW - Latent semantic analysis

KW - Remote homology detection

KW - Support vector machine

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U2 - 10.1109/ICBECS.2010.5462512

DO - 10.1109/ICBECS.2010.5462512

M3 - Conference contribution

AN - SCOPUS:77953320348

SN - 9781424453153

T3 - 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

BT - 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

T2 - 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

Y2 - 23 April 2010 through 25 April 2010

ER -

Protein fold recognition and remote homology detection based on profile-level building blocks

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Keywords

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