Briefings in Bioinformatics | VOL. 23
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Computational models, databases and tools for antibiotic combinations

Publication Date Aug 1, 2022

Abstract

Abstract Antibiotic combination is a promising strategy to extend the lifetime of antibiotics and thereby combat antimicrobial resistance. However, screening for new antibiotic combinations is both time-consuming and labor-intensive. In recent years, an increasing number of researchers have used computational models to predict effective antibiotic combinations. In this review, we summarized existing computational models for antibiotic combinations and discussed the limitations and challenges of these models in detail. In addition, we also collected and summarized available data resources and tools for antibiotic combinations. This study aims to help computational biologists design more accurate and interpretable computational models.

Concepts

Antibiotic Combinations Computational Models Models In Detail Data Resources Screening For Combinations Models For Combinations Computational Databases Interpretable Models Computational Tools Accurate Models

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