This program reads a fasta file specified by -i option, then, converts it to SVM Light format, further runs the classification module of SVM Light and then evaluate the predictions.
The support vector machine models were based on 310 antimicrobial peptide sequences extracted from antimicrobial peptides database and 310 non-antimicrobial peptide sequences extracted from protein data bank. The system's accuracy is 90% by using the polynomial model (default).
Follow CS-AMPPred
Other Useful Business Software
Custom VMs From 1 to 96 vCPUs With 99.95% Uptime
Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of CS-AMPPred!