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
Diabetes fact sheet
World Health Organisation, 2015
Accelerating Metropolis-Hastings algorithms by delayed acceptance
M Banterle, C Grazian, A Lee, CP Robert
arXiv preprint arXiv:1503.00996, 2015
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics
PLoS Biology 20 (8), 2022
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
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
Approximate Bayesian inference in semiparametric copula models
C Grazian, B Liseo
Approximating the Likelihood in ABC
CC Drovandi, C Grazian, K Mengersen, C Robert
Handbook of approximate bayesian computation, 321-368, 2018
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
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
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
Accelerating Metropolis-Hastings algorithms: Delayed acceptance with prefetching
M Banterle, C Grazian, CP Robert
arXiv preprint arXiv:1406.2660, 2014
Darwin series: Domain specific large language models for natural science
T Xie, Y Wan, W Huang, Z Yin, Y Liu, S Wang, Q Linghu, C Kit, C Grazian, ...
arXiv preprint arXiv:2308.13565, 2023
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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Articles 1–20