AntiDMPpred is predictor based on random forest (RF) for identifying anti-diabetic peptides. The framework of AntiDMPpred is illustrated in the following figure.
AntiDMPpred allows users to submit peptide sequences in fasta or plain text format and set the threshold of probability value to differentiate between predicted positives and negatives (tp). Performance of AntiDMPpred in the training dataset when tp changes are displayed in a table.
When tp=0.5, the predicted results of peptides pep1, pep1, pep3 are shown in the following figure.
Number: the serial number of the query sequence;
Query Sequence: the sequence of the query peptide;
Length: the length of the query sequence;
Probability: the probability value that the query sequence is predicted to be an anti-diabetic peptide;
Yes/No: the "Yes/No" column shows the prediction result, when the "Probability" is greater than or equal to "tp", the column is displayed as "Yes", which indicates that the sequence is predicted to be an anti-diabetic peptide; otherwise "No".