AGRAMP: machine learning models for predicting antimicrobial peptides against phytopathogenic bacteria
IntroductionAntimicrobial peptides (AMPs) are promising alternatives to traditional antibiotics for combating plant pathogenic bacteria in agriculture and the environment. However, identifying potent AMPs through laborious experimental assays is resource-intensive and time-consuming. To address thes...
Main Authors: | Jonathan Shao, Yan Zhao, Wei Wei, Iosif I. Vaisman |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2024-03-01
|
Series: | Frontiers in Microbiology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2024.1304044/full |
Similar Items
-
Efficacy of <i>Trichoderma longibrachiatum</i> Trichogin GA IV Peptaibol analogs against the Black Rot Pathogen <i>Xanthomonas campestris</i> pv. <i>campestris</i> and other Phytopathogenic Bacteria
by: Rocco Caracciolo, et al.
Published: (2023-02-01) -
Atomic-Resolution Structures and Mode of Action of Clinically Relevant Antimicrobial Peptides
by: Surajit Bhattacharjya, et al.
Published: (2022-04-01) -
The Development of New Methods to Stimulate the Production of Antimicrobial Peptides in the Larvae of the Black Soldier Fly <i>Hermetia illucens</i>
by: Atsuyoshi Nakagawa, et al.
Published: (2023-10-01) -
Antimicrobial Peptides as Anticancer Agents: Functional Properties and Biological Activities
by: Anna Lucia Tornesello, et al.
Published: (2020-06-01) -
Antimicrobial properties of tomato juice and peptides against typhoidal Salmonella
by: Ryan S. Kwon, et al.
Published: (2024-03-01)