BaPreS: a software tool for predicting bacteriocins using an optimal set of features.

ABSTRACT:

Background

Antibiotic resistance is a major public health concern around the globe. As a result, researchers always look for new compounds to develop new antibiotic drugs for combating antibiotic-resistant bacteria. Bacteriocin becomes a promising antimicrobial agent to fight against antibiotic resistance, due to cases of both broad and narrow killing spectra. Sequence matching methods are widely used to identify bacteriocins by comparing them with the known bacteriocin sequences; however, these methods often fail to detect new bacteriocin sequences due to their high diversity. The ability to use a machine learning approach can help find new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. The aim of this work is to develop a machine learning-based s

SUBMITTER: Akhter S 

PROVIDER: S-EPMC10433575 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature