| 1 | Oxypred:Prediction and Classification of Oxygen-Binding Proteins显示文摘This study describes a method for predicting and classifying oxygen-binding pro-teins. Firstly,support vector machine (SVM) modules were developed using amino acid composition and dipeptide composition for predicting oxygen-binding pro-teins,and achieved maximum accuracy of 85.5% and 87.8%,respectively. Sec-ondly,an SVM module was developed based on amino acid composition,classify-ing the predicted oxygen-binding proteins into six classes with accuracy of 95.8%,97.5%,97.5%,96.9%,99.4%,and 96.0% for erythrocruorin,hemerythrin,hemo-cyanin,hemoglobin,leghemoglobin,and myoglobin proteins,respectively. Finally,an SVM module was developed using dipeptide composition for classifying the oxygen-binding proteins,and achieved maximum accuracy of 96.1%,98.7%,98.7%,85.6%,99.6%,and 93.3% for the above six classes,respectively. All modules were trained and tested by five-fold cross validation. Based on the above approach,a web server Oxypred was developed for predicting and classifying oxygen-binding proteins (available from http://www.imtech.res.in/raghava/oxypred/). | S.Muthukrishnan Aarti Garg G.P.S.Raghava | 2007 | Genomics, Proteomics & Bioinformatics2007，5，3： | 0 |
| 2 | VGIchan:Prediction and Classification of Voltage-Gated Ion Channels显示文摘This study describes methods for predicting and classifying voltage-gated ion chan-nels. Firstly, a standard support vector machine (SVM) method was developed forpredicting ion channels by using amino acid composition and dipeptide composi-tion, with an accuracy of 82.89% and 85.56%, respectively. The accuracy of thisSVM method was improved from 85.56% to 89.11% when combined with PSI-BLAST similarity search. Then we developed an SVM method for classifying ionchannels (potassium, sodium, calcium, and chloride) by using dipeptide compo-sition and achieved an overall accuracy of 96.89%. We further achieved a clas-sification accuracy of 97.78% by using a hybrid method that combines dipeptide-based SVM and hidden Markov model methods. A web server VGIchan has beendeveloped for predicting and classifying voltage-gated ion channels using the aboveapproaches. VGIchan is freely available at www.imtech.res.in/raghava/vgichan/. | Sudipto Saha Jyoti Zack Balvinder Singh G.P.S.Raghava | 2006 | Genomics, Proteomics & Bioinformatics2006，4，4： | 0 |
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