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Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data., , , , , , , , , and 1 other author(s). Bioinform., 34 (10): 1666-1671 (2018)DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis., , , , , , , , , and . Bioinform., 35 (18): 3240-3249 (2019)ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes., and . PLoS Comput. Biol., (2015)Detection of Mixed Infection from Bacterial Whole Genome Sequence Data Allows Assessment of Its Role in Clostridium difficile Transmission., , , , , , and . PLoS Comput. Biol., (2013)Bayesian reconstruction of transmission within outbreaks using genomic variants., , , and . PLoS Comput. Biol., (2018)Application of machine learning techniques to tuberculosis drug resistance analysis., , , , , , , , and . Bioinform., 35 (13): 2276-2282 (2019)SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent., , and . PLoS Comput. Biol., (2016)Practical Approaches for Detecting Selection in Microbial Genomes., and . PLoS Comput. Biol., (2016)Sequential Monte Carlo with transformations., , , and . Stat. Comput., 30 (3): 663-676 (2020)Distribution of serogroups and genotypes among disease-associated and carried isolates of Neisseria meningitidis from the Czech Republic, Greece, and Norway, , , , , , , , , and 2 other author(s). Journal of Clinical Microbiology, 42 (11): 5146--53 (November 2004)PMID: 15528708.