Deep learning regression model for antimicrobial peptide design
A CNN trained on 4050 E. coli peptide MIC records predicts activity, outperformed other AMP classifiers with random negatives, and guided two designed peptides active against three pathogens.
bioRxiv · Jul 12, 2019 · PreprintBioinformatics✦ In-depth digest