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• W2010125744 endingPage "373" @default.
• W2010125744 startingPage "365" @default.
• W2010125744 abstract "This is the continuation of our studies on the prediction of mutation engineered by randomness in proteins from influenza A virus. In our previous studies, we have demonstrated that randomness plays a role in engineering mutations because the measures of randomness in protein are different before and after mutations. Thus we built a cause-mutation relationship to count the mutation engineered by randomness, and conducted several concept-initiated studies to predict the mutations in proteins from influenza A virus, which demonstrated the possibility of prediction of mutations along this line of thought. On the other hand, these concept-initiated studies indicate the directions forwards the enhancement of predictability, of which we need to use the neural network instead of logistic regression that was used in those concept-initiated studies to enhance the predictability. In this proof-of-concept study, we attempt to apply the neural network to modeling the cause-mutation relationship to predict the possible mutation positions, and then we use the amino acid mutating probability to predict the would-be-mutated amino acids at predicted positions. The results confirm the possibility of use of internal cause-mutation relationship with neural network model to predict the mutation positions and use of amino acid mutating probability to predict the would-be-mutated amino acids." @default.
• W2010125744 created "2016-06-24" @default.
• W2010125744 creator A5034316640 @default.
• W2010125744 creator A5044041420 @default.
• W2010125744 date "2007-11-02" @default.
• W2010125744 modified "2023-10-12" @default.
• W2010125744 title "Prediction of mutations engineered by randomness in H5N1 hemagglutinins of influenza A virus" @default.
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• W2010125744 doi "https://doi.org/10.1007/s00726-007-0602-4" @default.
• W2010125744 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7088403" @default.
• W2010125744 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/17973072" @default.
• W2010125744 hasPublicationYear "2007" @default.
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