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Email

michael.hall2@unimelb.edu.au

Credentials


Position
Honorary (Fellow)
Department of Microbiology and Immunology
Education
PhD
University of Cambridge
Masters (Coursework & Research)
University of Queensland
Bachelors Degree
Queensland University of Technology
ORCID

0000-0003-3683-6208

Dr Michael Hall

Honorary (Fellow)
Department of Microbiology and Immunology

37 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Efficient downsampling of genome alignments with Rasusa
    DOI: 10.46471/gigabyte.180
  • 2025

    Journal article

    Genome size estimation from long read overlaps
    DOI: 10.1093/bioinformatics/btaf593
  • 2025

    Journal article

    Sustainable data analysis with Snakemake
    DOI: 10.12688/f1000research.29032.3
  • 2025

    Journal article

    TBpore cluster: A novel phylogenetic pipeline for tuberculosis transmission studies using nanopore next-generation sequencing data
    DOI: 10.1371/journal.pone.0325914
  • 2025

    Journal article

    Sustainable data analysis with Snakemake
    DOI: 10.12688/f1000research.29032.3
  • 2025

    Journal article

    Genome graphs reveal the importance of structural variation in Mycobacterium tuberculosis evolution and drug resistance
    DOI: 10.1038/s41467-025-65779-9
  • 2024

    Journal article

    Pseudo-éclosion de Mycobacterium tuberculosis due à une contamination croisée en laboratoire : une investigation d'éclosion en épidémiologie moléculaire
    DOI: 10.14745/ccdr.v50i12da03f
Michael Hall

RECENT SCHOLARLY WORKS

  • 2024

    Journal article

    Whole genome sequencing of M. tuberculosis for disease control in high-burden settings: study protocol for a cluster randomized controlled trial evaluating different community-wide intervention strategies in rural Madagascar
    DOI: 10.1186/s13063-024-08537-4
  • 2024

    Journal article

    Mycobacterium tuberculosis pseudo-outbreak due to laboratory cross-contamination: A molecular epidemiology outbreak investigation.
    DOI: 10.14745/ccdr.v50i12da03
  • 2024

    Journal article

    Benchmarking reveals superiority of deep learning variant callers on bacterial nanopore sequence data
    DOI: 10.7554/elife.98300.3

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