scholarly journals DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Bin Liu ◽  
Shanyi Wang ◽  
Xiaolong Wang
Keyword(s):  
Amino Acid ◽  
Dna Binding ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Protein Identification ◽  
Binding Protein ◽  
Dna Binding Protein ◽  
Pseudo Amino Acid Composition

scholarly journals Prediction of Aptamer-Target Interacting Pairs with Pseudo-Amino Acid Composition

PLoS ONE ◽  
2014 ◽  
Vol 9 (1) ◽  
pp. e86729 ◽  
Author(s):  
Bi-Qing Li ◽  
Yu-Chao Zhang ◽  
Guo-Hua Huang ◽  
Wei-Ren Cui ◽  
Ning Zhang ◽  
...  
Keyword(s):  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Pseudo Amino Acid Composition

scholarly journals KK-DBP: A Multi-Feature Fusion Method for DNA-Binding Protein Identification Based on Random Forest

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuran Jia ◽  
Shan Huang ◽  
Tianjiao Zhang
Keyword(s):  
Dna Binding ◽  
Prediction Accuracy ◽  
Large Scale ◽  
Protein Identification ◽  
Feature Fusion ◽  
Binding Protein ◽  
Rapid Development ◽  
Dna Binding Protein ◽  
Feature Extraction Method ◽  
Independent Test Dataset

DNA-binding protein (DBP) is a protein with a special DNA binding domain that is associated with many important molecular biological mechanisms. Rapid development of computational methods has made it possible to predict DBP on a large scale; however, existing methods do not fully integrate DBP-related features, resulting in rough prediction results. In this article, we develop a DNA-binding protein identification method called KK-DBP. To improve prediction accuracy, we propose a feature extraction method that fuses multiple PSSM features. The experimental results show a prediction accuracy on the independent test dataset PDB186 of 81.22%, which is the highest of all existing methods.

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