AIMC Topic: Antitubercular Agents
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First-line drug resistance profiling of : a machine learning approach.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 21, 2022
The persistence and emergence of new multi-drug resistant Mycobacterium tuberculosis (M. tb) strains continues to advance the devastating tuberculosis (TB) epidemic. Robust systems are needed to accurately and rapidly perform drug-resistance profilin...
Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.
Scientific reports
Feb 14, 2022
Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic s...
Mycobacterium abscessus drug discovery using machine learning.
Tuberculosis (Edinburgh, Scotland)
Jan 20, 2022
The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tuberculosis in the United States and much of the developed world. Nontuberculous mycobacteria occur naturally in the environment and are a significant proble...
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...
Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.
Molecular diversity
Jun 10, 2021
Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emerging cases of drug resistance among pathogenic mycobacteria have been a global threat urging the need of new drug discovery and development. However, ...
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...
Evaluation of magnesium oxide and zinc oxide nanoparticles against multi-drug-resistance Mycobacterium tuberculosis.
The Indian journal of tuberculosis
Aug 4, 2020
OBJECTIVE: The current study has evaluated the MICs and MBCs of ZnONPs, MgONPs, and MgONPs-ZnONPs against HRv Mtb and MDR-Mtb.
A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries.
Tuberculosis (Edinburgh, Scotland)
Jun 23, 2020
Tuberculosis is ranked as the 2nd deadliest disease in the world and is responsible for ten million deaths in 2017. Treatment failure is one of a main reason behind these deaths. Reasons of treatment failure are still unknown and the death rate due t...
Comparison of the predictive outcomes for anti-tuberculosis drug-induced hepatotoxicity by different machine learning techniques.
Computer methods and programs in biomedicine
Dec 27, 2019
BACKGROUND: The study compared the predictive outcomes of artificial neural network, support vector machine and random forest on the occurrence of anti-tuberculosis drug-induced hepatotoxicity.
Genomics
Genotype
Support Vector Machine
Liver
Taiwan
Female
Antitubercular Agents
Reproducibility of Results
Tuberculosis
Risk Factors
Male
Aged
Aged, 80 and over
Middle Aged
Gene Frequency
Humans
Adult
Drug Discovery
Polymorphism, Genetic
Neural Networks, Computer
Sensitivity and Specificity
ROC Curve
Chemical and Drug Induced Liver Injury
Machine Learning
Antitubercular metabolites from the marine-derived fungus strain MF029.
Natural product research
Sep 6, 2019
During the systematic screening of bioactive compounds from our marine natural product library, crude extract of the marine-derived fungus strain MF029 exhibited moderate bioactivities against , S, methicillin-resistant , and bacillus Calmette-Guér...
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