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

Auto Covariance combined with Artificial Neural Network for predicting Protein-Protein interactions

Authors
Juanjuan Li, Yuehui Chen
Corresponding Author
Juanjuan Li
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.153How to use a DOI?
Keywords
predicting PPIs, auto covariance, ANN
Abstract
Proteins play biological function through the interactions in organisms. Proteins are major components of organisms, and they are of great significance. As an increasing number of high-throughput biological experiments are carried out, a large amount of biological data is produced. Bioinformatics is developed to study the relative data which turns out to be difficult to study using biological methods. The paper mainly studies how to apply the intelligent calculation methods to protein- protein interactions (PPIs) prediction. We proposed an approach, by combining auto covariance with artificial neural network classifier, to predict PPIs. Experiments show that our method performs better than related works with a 5% higher accuracy.
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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.2013.153How 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  - Juanjuan Li
AU  - Yuehui Chen
PY  - 2013/04
DA  - 2013/04
TI  - Auto Covariance combined with Artificial Neural Network for predicting Protein-Protein interactions
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.153
DO  - https://doi.org/10.2991/icsem.2013.153
ID  - Li2013/04
ER  -