In:
mSystems, American Society for Microbiology
Kurzfassung:
Antimicrobial peptides (AMPs) are potential candidates for replacing conventional antibiotics to combat drug resistance in pathogenic bacteria. Therefore, it is necessary to evaluate the antimicrobial activity of AMPs quantitatively. However, wet-lab experiments are labor-intensive and time-consuming. To accelerate the evaluation process, we develop a deep learning method called MBC-Attention to regress the experimental minimum inhibitory concentration of AMPs against Escherichia coli . The proposed model outperforms traditional machine learning methods. Data, scripts to reproduce experiments, and the final production models are available on GitHub.
Materialart:
Online-Ressource
ISSN:
2379-5077
DOI:
10.1128/msystems.00345-23
Sprache:
Englisch
Verlag:
American Society for Microbiology
Publikationsdatum:
2023
ZDB Id:
2844333-0