Clara Grazian
Cited by
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The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis
TM Walker, P Miotto, CU Köser, PW Fowler, J Knaggs, Z Iqbal, M Hunt, ...
The Lancet Microbe 3 (4), e265-e273, 2022
Validating a 14-drug microtiter plate containing bedaquiline and delamanid for large-scale research susceptibility testing of Mycobacterium tuberculosis
PMV Rancoita, F Cugnata, AL Gibertoni Cruz, E Borroni, SJ Hoosdally, ...
Antimicrobial agents and chemotherapy 62 (9), 10.1128/aac. 00344-18, 2018
Application of machine learning techniques to tuberculosis drug resistance analysis
DACCC Samaneh Kouchaki, Yang Yang, T Walker, A Sarah Walker, Daniel J Wilson ...
Bioinformatics 35 (13), 2276-2282, 2019
Accelerating Metropolis-Hastings algorithms by delayed acceptance
M Banterle, C Grazian, A Lee, CP Robert
arXiv preprint arXiv:1503.00996, 2015
Epidemiological cut-off values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis
CRyPTIC Consortium
European Respiratory Journal 60 (4), 2022
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics
PLoS Biology 20 (8), 2022
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
DAC Yang Yang, Timothy M Walker, A Sarah Walker, Daniel J Wilson, Timothy E ...
Bioinformatics, 1-10, 2019
Genome-wide association studies of global Mycobacterium tuberculosis resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms
PLoS Biology 20 (8), 2022
GenomegaMap: within-species genome-wide d_N/d_S estimation from over 10,000 genomes
Molecular Biology and Evolution, 2020
GenomegaMap: within-species genome-wide d_N/d_S estimation from over 10,000 genomes
Molecular Biology and Evolution, 2020
Catalogue of mutations in Mycobacterium tuberculosis complex and their association with drug resistance
World Health Organization, 2021
Approximating the Likelihood in ABC
CC Drovandi, C Grazian, K Mengersen, C Robert
Handbook of approximate bayesian computation, 321-368, 2018
Approximate Bayesian inference in semiparametric copula models
C Grazian, B Liseo
A review of approximate Bayesian computation methods via density estimation: Inference for simulator‐models
C Grazian, Y Fan
Wiley Interdisciplinary Reviews: Computational Statistics 12 (4), e1486, 2020
Jeffreys priors for mixture estimation: Properties and alternatives
C Grazian, CP Robert
Computational Statistics & Data Analysis 121, 149-163, 2018
Bedaquiline and clofazimine resistance in Mycobacterium tuberculosis: an in-vitro and in-silico data analysis
L Sonnenkalb, JJ Carter, A Spitaleri, Z Iqbal, M Hunt, KM Malone, ...
The Lancet Microbe 4 (5), e358-e368, 2023
Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes
Z Hunt, M., Letcher, B., Malone, K. M., Nguyen, G., Hall, M. B., Colquhoun ...
Genome Biology 23 (1), 1-23, 2022
Accelerating Metropolis-Hastings algorithms: Delayed acceptance with prefetching
M Banterle, C Grazian, CP Robert
arXiv preprint arXiv:1406.2660, 2014
Jeffreys’ priors for mixture estimation
C Grazian, CP Robert
Bayesian Statistics from Methods to Models and Applications: Research from …, 2015
On a loss-based prior for the number of components in mixture models
C Grazian, C Villa, B Liseo
Statistics & Probability Letters 158, 108656, 2020
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