2nd International Conference On Systems Engineering and Modeling (ICSEM-13)

Predict the Tertiary Structure of Protein with Binary Tree and Ensemble Strategy

Authors
Yiming Chen, Yuehui Chen
Corresponding Author
Yiming Chen
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.120How to use a DOI?
Keywords
tertiary structure,binary tree, selective ensemble,FNT
Abstract
In this paper we intend to apply a new method to predict tertiary structure. Several feature extraction methods adopted are physicochemical composition, recurrence quantification analysis (RQA) , pseudo amino acid composition (PseAA) and Distance frequency. We construct the binary tree Classification model, and adopt flexible neural tree models as the classifiers. We will train a number of based classifiers through different features extraction methods for every node of binary tree, then employ the selective ensemble method to ensemble them. 640 dataset is selected to our experiment. The predict accuracy with our method on this data set is 63.58%, higher than some other methods on the 640 datasets. So, our method is feasible and effective in some extent.
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Proceedings
2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-94-91216-42-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/icsem.2013.120How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yiming Chen
AU  - Yuehui Chen
PY  - 2013/04
DA  - 2013/04
TI  - Predict the Tertiary Structure of Protein with Binary Tree and Ensemble Strategy
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.120
DO  - https://doi.org/10.2991/icsem.2013.120
ID  - Chen2013/04
ER  -