Integrative bioinformatics, machine learning, and molecular docking identify HigBA toxin-antitoxin systems as key mediators of quorum sensing in Acinetobacter baumannii.
- DOI
- 10.1016/j.compbiolchem.2026.109362
- Published
- 2026-08-26
- Container
- Comput Biol Chem
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- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.compbiolchem.2026.109362,
title = {Integrative bioinformatics, machine learning, and molecular docking identify HigBA toxin-antitoxin systems as key mediators of quorum sensing in Acinetobacter baumannii.},
author = {Osaghale L and Beshiru A and Edafetanure-Ibeh OM and Ajoseh SO and Duggal AP.},
year = {2026},
journal = {Comput Biol Chem},
doi = {10.1016/j.compbiolchem.2026.109362},
url = {https://doi.org/10.1016/j.compbiolchem.2026.109362}
}RIS
TY - JOUR TI - Integrative bioinformatics, machine learning, and molecular docking identify HigBA toxin-antitoxin systems as key mediators of quorum sensing in Acinetobacter baumannii. AU - Osaghale L AU - Beshiru A AU - Edafetanure-Ibeh OM AU - Ajoseh SO AU - Duggal AP. PY - 2026 JO - Comput Biol Chem DO - 10.1016/j.compbiolchem.2026.109362 UR - https://doi.org/10.1016/j.compbiolchem.2026.109362 ER -
APA
L, O., A, B., OM, E., SO, A., & AP., D. (2026). Integrative bioinformatics, machine learning, and molecular docking identify HigBA toxin-antitoxin systems as key mediators of quorum sensing in Acinetobacter baumannii.. Comput Biol Chem. https://doi.org/10.1016/j.compbiolchem.2026.109362
Source records
- europe-pmc · retrieved 2026-09-26T03:22:16.181Z