Efficient ensemble schemes for protein secondary structure prediction

Kun Hong Liu; Jun Feng Xia; Xueling Li

doi:10.2174/092986608784567546

Efficient ensemble schemes for protein secondary structure prediction

Kun Hong Liu
, Jun Feng Xia
, Xueling Li

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.

Original language	English (US)
Pages (from-to)	488-493
Number of pages	6
Journal	Protein and Peptide Letters
Volume	15
Issue number	5
DOIs	https://doi.org/10.2174/092986608784567546
State	Published - Jun 2008
Externally published	Yes

Keywords

Classifier ensemble system
Multiple sequence alignment
Neural network
Protein secondary structure prediction

ASJC Scopus subject areas

Structural Biology
Biochemistry

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10.2174/092986608784567546

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title = "Efficient ensemble schemes for protein secondary structure prediction",

abstract = "This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.",

keywords = "Classifier ensemble system, Multiple sequence alignment, Neural network, Protein secondary structure prediction",

author = "Liu, \{Kun Hong\} and Xia, \{Jun Feng\} and Xueling Li",

year = "2008",

month = jun,

doi = "10.2174/092986608784567546",

language = "English (US)",

volume = "15",

pages = "488--493",

journal = "Protein and Peptide Letters",

issn = "0929-8665",

publisher = "Bentham Science Publishers",

number = "5",

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T1 - Efficient ensemble schemes for protein secondary structure prediction

AU - Liu, Kun Hong

AU - Xia, Jun Feng

AU - Li, Xueling

PY - 2008/6

Y1 - 2008/6

N2 - This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.

AB - This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.

KW - Classifier ensemble system

KW - Multiple sequence alignment

KW - Neural network

KW - Protein secondary structure prediction

UR - https://www.scopus.com/pages/publications/45749117507

UR - https://www.scopus.com/pages/publications/45749117507#tab=citedBy

U2 - 10.2174/092986608784567546

DO - 10.2174/092986608784567546

M3 - Article

C2 - 18537739

AN - SCOPUS:45749117507

SN - 0929-8665

VL - 15

SP - 488

EP - 493

JO - Protein and Peptide Letters

JF - Protein and Peptide Letters

IS - 5

ER -

Efficient ensemble schemes for protein secondary structure prediction

Abstract

Keywords

ASJC Scopus subject areas

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