Àá½Ã¸¸ ±â´Ù·Á ÁÖ¼¼¿ä. ·ÎµùÁßÀÔ´Ï´Ù.
KMID : 0624620100430100670
BMB Reports
2010 Volume.43 No. 10 p.670 ~ p.676
A novel method for predicting protein subcellular localization based on pseudo amino acid composition
Ma Junwei

Gu Hong
Abstract
In this paper, a novel approach, ELM-PCA, is introduced for the first time to predict protein subcellular localization. Firstly, Protein Samples are represented by the pseudo amino acid composition (PseAAC). Secondly, the principal component analysis (PCA) is employed to extract essential features. Finally, the Elman Recurrent Neural Network (RNN) is used as a classifier to identify the protein sequences. The results demonstrate that the proposed approach is effective and practical.
KEYWORD
Elman neural network, Five-fold cross validation, Principal component analysis, Protein subcellular localization, Pseudo amino acid composition
FullTexts / Linksout information
Listed journal information
SCI(E) ÇмúÁøÈïÀç´Ü(KCI) ´ëÇÑÀÇÇÐȸ ȸ¿ø