Algorithms
SVM
The SVM was implemented using freely downloadable software package SVM_light written by Joachims (Joachims 1999). The software enables the user to define a number of parameters as well as to select from a choice of inbuilt kernal functions, including a radial basis function (RBF) and a polynomial kernal.
Evaluation Modules
The performance modules constructed in this study were evaluated using a 5-fold cross-validation technique. In the 5-fold cross-validation, the relevant dataset was partoned randomly into five equally sized sets. The training and testing was carried out five times, each time using one distinct set for testing and the remaining four sets for training.The performance of the methods was computed using the following formulas:
Sensitivity = (TP / (TP+FN))*100
Specificity = (TN / (TN+FP))*100
Accuracy = (TP+TN / (TP+FP+TN+FN))*100
Where TP and TN are correctly predict Aminoacyl tRNA synthetases and non-aminoacyl tRNA synthetases respectively. FP and FN are wrongly predicted Aminoacyl tRNA synthetases and non-aminoacyl tRNA synthetases respectively.