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• W2291567276 abstract "Since the apoptosis protein plays an important role in understanding the mechanism of programmed cell death, so further to reveal the mechanism of subclass for apoptosis can bring more insights to their function. Here, our group established a dataset included 239 anti-apoptosis proteins and 222 pro-apoptosis proteins in our previous work. The extraction of information based on sequence information, gene ontology information and evolution information. Finally we proposed a mean value k-nearest neighbor (MKNN) algorithm. The results of MKNN indicated that the decision-making method of mean value is distinctly superior to the traditional decision-making method of majority vote. Meanwhile, we also listed the result of support vector machine (SVM) and k-nearest neighbor (KNN) to compare with our method. Then jackknife tests show that improved method is robust, useful and reliable for predicting the subcellular location of protein." @default.
• W2291567276 created "2016-06-24" @default.
• W2291567276 creator A5006346562 @default.
• W2291567276 creator A5030338153 @default.
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• W2291567276 date "2015-10-01" @default.
• W2291567276 modified "2023-09-27" @default.
• W2291567276 title "Using improved K-nearest neighbor method to identify anti-and pro-apoptosis proteins" @default.
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• W2291567276 doi "https://doi.org/10.1109/bmei.2015.7401566" @default.
• W2291567276 hasPublicationYear "2015" @default.
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