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

DOI

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 748
EP  - 750
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.153
DO  - 10.2991/icsem.2013.153
ID  - Li2013/04
ER  -