ProtRe-CN: Protein Remote Homology Detection by Combining Classification Methods and Network Methods via Learning to Rank

2021 ◽  
pp. 1-1
Author(s):  
Jiangyi Shao ◽  
Junjie Chen ◽  
Bin Liu
Keyword(s):  
Learning To Rank ◽  
Classification Methods ◽  
Homology Detection ◽  
Remote Homology ◽  
Network Methods ◽  
Remote Homology Detection

scholarly journals Application of learning to rank to protein remote homology detection

2015 ◽  
Vol 31 (21) ◽  
pp. 3492-3498 ◽  
Author(s):  
Bin Liu ◽  
Junjie Chen ◽  
Xiaolong Wang
Keyword(s):  
Learning To Rank ◽  
Homology Detection ◽  
Remote Homology ◽  
Remote Homology Detection

Optimizing Discriminant Model for Improved Classification of Protein

2013 ◽  
Vol 411-414 ◽  
pp. 3227-3231
Author(s):  
Dong Wang ◽  
Ting Song ◽  
Bin Liu
Keyword(s):  
Protein Classification ◽  
Classification Methods ◽  
Homology Detection ◽  
Training Set ◽  
Remote Homology ◽  
Discriminant Model ◽  
Classifier Performance ◽  
Remote Homology Detection

Classifiers based on discriminant model achieved the highest accuracy compared to other protein classification methods in remote homology detection, but all of the classifiers were troubled by imbalance training in modeling. This paper presented a protein classification based on optimization of discriminant model to further improve the classifier performance by setting different penalty coefficients for the positive and negative samples to balance the training set weights. Comparative experiments show that the method based on optimized discriminant model obtained higher accuracy, and the method can improve the performance of all classifiers based on discriminant model by optimization of the parameters.

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