We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is feature...We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is featured by fusing multiple individual predictors, each of which is established based on one special feature derived from the protein sequence. The ensemble pre-dictor thus formed is superior to the individual ones, as demonstrated by achieving higher correlation coefficient and lower root mean square deviation between the predicted and observed results when examined by the jack-knife cross-validation on a benchmark dataset constructed recently. As a user-friendly web- server, Pred-PFR is freely accessible to the public at www.csbio.sjtu.edu.cn/bioinf/Folding Rate/.展开更多
We present a methodology for constructing a short-term event risk score in heart failure patients from an ensemble predictor, using bootstrap samples, two different classification rules, logistic regression and linear...We present a methodology for constructing a short-term event risk score in heart failure patients from an ensemble predictor, using bootstrap samples, two different classification rules, logistic regression and linear discriminant analysis for mixed data, continuous or categorical, and random selection of explanatory variables to build individual predictors. We define a measure of the importance of each variable in the score and an event risk measure by an odds-ratio. Moreover, we establish a property of linear discriminant analysis for mixed data. This methodology is applied to EPHESUS trial patients on whom biological, clinical and medical history variables were measured.展开更多
文摘We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is featured by fusing multiple individual predictors, each of which is established based on one special feature derived from the protein sequence. The ensemble pre-dictor thus formed is superior to the individual ones, as demonstrated by achieving higher correlation coefficient and lower root mean square deviation between the predicted and observed results when examined by the jack-knife cross-validation on a benchmark dataset constructed recently. As a user-friendly web- server, Pred-PFR is freely accessible to the public at www.csbio.sjtu.edu.cn/bioinf/Folding Rate/.
文摘We present a methodology for constructing a short-term event risk score in heart failure patients from an ensemble predictor, using bootstrap samples, two different classification rules, logistic regression and linear discriminant analysis for mixed data, continuous or categorical, and random selection of explanatory variables to build individual predictors. We define a measure of the importance of each variable in the score and an event risk measure by an odds-ratio. Moreover, we establish a property of linear discriminant analysis for mixed data. This methodology is applied to EPHESUS trial patients on whom biological, clinical and medical history variables were measured.
