doi: 10.7763/IJMLC.2012.V2.238
Classification of Protein 3D Structures Using Artificial Neural Network
Hui Li1
,
Chunmei Liu1 ,
Legand Burge1 ,
William Southerland2
- 1Department of Systems and Computer Science, Howard University, Washington, DC 20059, USA.
- 2Department of Biochemistry and Molecular Biology Howard University, Washington, DC 20059, USA.
Abstract
Three dimensional (3D) protein structures determine the function of a protein within a cell. Classification of 3D structure of proteins is therefore crucial to inferring protein functional information as well as the evolution of interactions between proteins. In this paper, we utilized the artificial neural network (ANN) paradigm to classify the protein structures. The approach equally divides a 3D protein structure into several parts and then extracts statistical features from each part. The different parts in spatial domain are thus viewed as the feature vectors which are input into the neural network. The computational experiments achieve better results in most cases than other currently existing approaches.
Keywords
- Protein
- structure;
- classification;
- ANN
How to Cite
Hui Li, Chunmei Liu, Legand Burge, and William Southerland, "Classification of Protein 3D Structures Using Artificial Neural Network," International Journal of Machine Learning, vol. 2, no. 6, pp. 791-793, 2012. https://doi.org/10.7763/IJMLC.2012.V2.238
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).