AIMC Topic: Anti-Bacterial Agents

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Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery.

Journal of chemical information and modeling
Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecular featurization is key to all highly accurate learning models for antibiotic discovery. In this pa...

Nitric oxide releasing polyvinyl alcohol and sodium alginate hydrogels as antibacterial and conductive strain sensors.

International journal of biological macromolecules
Conductive hydrogels have promising applications in flexible electronic devices and artificial intelligence, which have attracted much attention in recent years. However, most conductive hydrogels have no antimicrobial activity, inevitably leading to...

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...

Membrane separation of antibiotics predicted with the back propagation neural network.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Antibiotics and antibiotic resistance genes (ARGs) have been frequently detected in the aquatic environment and are regarded as emerging pollutants. The prediction models for the removal effect of four target antibiotics by membrane separation techno...

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 ...

Addressing antibiotic resistance: computational answers to a biological problem?

Current opinion in microbiology
The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformati...

Prediction of vancomycin initial dosage using artificial intelligence models applying ensemble strategy.

BMC bioinformatics
BACKGROUND: Antibiotic resistance has become a global concern. Vancomycin is known as the last line of antibiotics, but its treatment index is narrow. Therefore, clinical dosing decisions must be made with the utmost care; such decisions are said to ...

Artificial intelligence and the potential for perioperative delabeling of penicillin allergies for neurosurgery inpatients.

British journal of neurosurgery
PURPOSE OF THE ARTICLE: Patients with penicillin allergy labels are more likely to have postoperative wound infections. When penicillin allergy labels are interrogated, a significant number of individuals do not have penicillin allergies and may be d...

Rational design of stapled antimicrobial peptides.

Amino acids
The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of traditional antibiotics. Structurally diverse antibiotics are urgently needed to combat multiple-resistant bacterial infections. As part of innate immu...