Article

Prediction of pyrazinamide resistance in <i>Mycobacterium tuberculosis</i> using structure-based machine learning approaches

2019-01-11

Abstract excerpt

<h4>Synopsis</h4> <h4>Background</h4> Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis, however antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA, an enzyme that converts pyrazinamide into its active form. <h4>Methods</h4> We curated a dataset of 664 non-redundant, missense amino acid muta...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8ffdf186-0243-5e2d-88f8-4e7ea583dc37
DOI: 10.1101/518142

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Prediction of pyrazinamide resistance in <i>Mycobacterium tuberculosis</i> using structure-based machine learning approachesDOI 10.1101/518142Read

Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine-learning approachesSemantic proximity Read

An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis.Semantic proximity Read

Mycobacterium tuberculosis pyrazinamide resistance determinants: a multicenter study.Semantic proximity Read

Regression for accurate and sensitive grading of mutations diagnostic of antibiotic resistance in<i>Mycobacterium tuberculosis</i>Semantic proximity Read

Rapidly and reproducibly building a comprehensive catalogue of resistance-associated variants for <i>M. tuberculosis</i>Semantic proximity Read

Predicting rifampicin resistance in <i>M. tuberculosis</i> using machine learning informed by protein structural and chemical featuresSemantic proximity Read

Structure guided prediction of Pyrazinamide resistance mutations in pncA.Semantic proximity Read

Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosis.Semantic proximity Read

Machine learning-based analysis of drug resistance mutations in Mycobacterium tuberculosis.Semantic proximity Read

A comprehensive characterization of PncA polymorphisms that confer resistance to pyrazinamide.Semantic proximity Read

Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.Semantic proximity Read

A modified decision tree approach to improve the prediction and mutation discovery for drug resistance in Mycobacterium tuberculosis.Semantic proximity Read