KK-DBP: A Multi-Feature Fusion Method for DNA-Binding Protein Identification Based on Random Forest
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TLDR
Wang et al. as mentioned in this paper developed a DNA-binding protein identification method called KK-DBP, which fuses multiple PSSM features to improve prediction accuracy and achieved a prediction accuracy of 81.22%.Abstract:
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.read more
Citations
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DNAPred_Prot: Identification of DNA-Binding Proteins Using Composition- and Position-Based Features
TL;DR: This work proposes a methodology named “DNAPred_Prot”, which uses various position and frequency-dependent features from protein sequences for efficient and effective prediction of DNA-binding proteins, and it can be predicted that the suggested methodology performs better than other extant methods.
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PlDBPred: a novel computational model for discovery of DNA binding proteins in plants
Upendra Kumar Pradhan,Prabina Kumar Meher,Sanchita Naha,Soumen Pal,Ajit Gupta,Rajender Parsad +5 more
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TL;DR: In this paper , a new three-part sequence-order feature extraction (TPSO) strategy is developed to extract more discriminative information from protein sequences for predicting the DNA-binding proteins.
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