AIMC Topic: Drug Resistance, Bacterial
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A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Multi-drug resistance (MDR) has become one of the greatest threats to human health worldwide, and novel treatment methods of infections caused by MDR bacteria are urgently needed. Phage therapy is a promising alternative to solve this problem, to whi...
GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.
Genome medicine
Aug 30, 2021
BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly...
Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.
mSphere
Aug 25, 2021
antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investiga...
Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach.
PLoS computational biology
Mar 29, 2021
To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demons...
Development and performance of CUHAS-ROBUST application for pulmonary rifampicin-resistance tuberculosis screening in Indonesia.
PloS one
Mar 25, 2021
BACKGROUND AND OBJECTIVES: Diagnosis of Pulmonary Rifampicin Resistant Tuberculosis (RR-TB) with the Drug-Susceptibility Test (DST) is costly and time-consuming. Furthermore, GeneXpert for rapid diagnosis is not widely available in Indonesia. This st...
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations.
Nature biomedical engineering
Mar 11, 2021
The de novo design of antimicrobial therapeutics involves the exploration of a vast chemical repertoire to find compounds with broad-spectrum potency and low toxicity. Here, we report an efficient computational method for the generation of antimicrob...
Mice, Inbred BALB C
Antimicrobial Cationic Peptides
Structure-Activity Relationship
Molecular Dynamics Simulation
Klebsiella pneumoniae
Klebsiella Infections
Escherichia coli
Staphylococcus aureus
Amino Acid Sequence
Pseudomonas aeruginosa
Acinetobacter baumannii
Drug Resistance, Bacterial
Female
Animals
Drug Design
Drug Discovery
Deep Learning
Microbial Sensitivity Tests
Mice
Anti-Bacterial Agents
The role of artificial intelligence in the battle against antimicrobial-resistant bacteria.
Current genetics
Feb 13, 2021
Antimicrobial resistance (AMR) in bacteria is a global health crisis due to the rapid emergence of multidrug-resistant bacteria and the lengthy development of new antimicrobials. In light of this, artificial intelligence in the form of machine learni...
Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches.
Scientific reports
Oct 22, 2020
Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce p...
Predicting antimicrobial resistance using conserved genes.
PLoS computational biology
Oct 19, 2020
A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features de...
Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.
Scientific reports
Sep 14, 2020
It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a ...
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