AIMC Topic: Drug Resistance, Bacterial

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ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

Microbiome
BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identific...

Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.

Chemosphere
Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept...

Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis.

Environment international
The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated acti...

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.

Molecular informatics
Increasing antimicrobial resistance (AMR) represents a global healthcare threat. To decrease the spread of AMR and associated mortality, methods for rapid selection of optimal antibiotic treatment are urgently needed. Machine learning (ML) models bas...

Antimicrobial resistance crisis: could artificial intelligence be the solution?

Military Medical Research
Antimicrobial resistance is a global public health threat, and the World Health Organization (WHO) has announced a priority list of the most threatening pathogens against which novel antibiotics need to be developed. The discovery and introduction of...

Deciphering complex antibiotic resistance patterns in through whole genome sequencing and machine learning.

Frontiers in cellular and infection microbiology
INTRODUCTION: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp us...

Anti-Biofilm: Machine Learning Assisted Prediction of IC Activity of Chemicals Against Biofilms of Microbes Causing Antimicrobial Resistance and Implications in Drug Repurposing.

Journal of molecular biology
Biofilms are one of the leading causes of antibiotic resistance. It acts as a physical barrier against the human immune system and drugs. The use of anti-biofilm agents helps in tackling the menace of antibiotic resistance. The identification of effi...

A historical, economic, and technical-scientific approach to the current crisis in the development of antibacterial drugs: Promising role of antibacterial peptides in this scenario.

Microbial pathogenesis
The emergence of antibiotic resistance (AMR) is a global public health problem. According to estimates, drug-resistant bacteria infect 2 million patients and perish 23,000 annually. To overcome this problem, antimicrobial peptides became a potential ...