FACR: Fungal Allergen Cross Reactivity Database

The statistical measures like Sensitivity, Specificity, Accuracy, Precision, Recall, Matthew’s Correlation coefficient (MCC) were used to evaluate the performance of different classifiers. MCC is a measure that is independent of several dependencies and the different classifiers are selected on the basis of MCC values. Values of MCC near to 0 indicates random predictions whereas its value near to 1 indicates accurate predictions. These measures for different classifiers are tabulated in the following table. The TPC classifier was judged the best among these three classifiers on the basis of MCC values. The users just have to download the zip files, unzip them on ubuntu or linux platforms having perl installed on it. Run the aac or dpc or tpc python program files (which ever you have downloaded) on the terminal, the graphical user interface will prompt on screen, where user can enter the query sequence in fasta format and click ok to run the program. After the program is executed the results will be shown on the message box of gui. For more information read the readme files.

Classifier Sensitivity Specificity Accuracy Precision MCC
AAC 85.77% 75% 81.53% 84.11% .62
DPC 86.96% 76.22% 82.73% 84.94% .64
TPC 84.98% 84.15% 84.65% 89.21% .68

 CLICK here to download model based on amino acid composition    

 CLICK here to download model based on dipeptide composition    

 CLICK here to download model based on tripeptide composition