Coin Laboratory: Genomics and bioinformatics in infectious disease and cancer

Research Overview

View a comprehensive listing of Professor Coin's research publications here.


The Coin Group develops genomic and transcriptomic tools to develop biomarkers for rapid characterization of disease state and prediction of drug susceptibility, with the aim of decreasing the time taken from hospital admission to administering the right treatment. We also develop biomarkers for measuring treatment response. We currently focus on infectious disease as well as cancer.

We utilize approaches from high-dimensional statistics, information theory and machine learning, including deep neural networks. We aim to implement streaming algorithms, which process data as soon as it is generated, providing real-time inference and visualization of both the most likely predicted disease state, as well as uncertainty in those predictions, which decrease as more data is collected.

Much of our current research utilizes real-time nanopore sequencing, based on its unique ability to generate sequence data in real-time, as well as its capability to sequence native DNA and RNA. We have emerging interests in single-cell long-read RNA and DNA sequencing, particularly as they relate to improving diagnostic and prognostic tools.

In infectious disease, we collaborate with chemists and materials scientists to develop techniques for isolating bacteria from complex biological matrices. We apply these approaches in conjunction with real-time nanopore sequencing to sequence bacterial genomes directly from clinical samples.

We have ongoing interests in evolution of complex regions of the genome, particularly highly repetitive regions. We are currently working utilizing long nanopore reads to characterize complex regions of tumour genomes inaccessible to short-read sequencing technologies.  We are interested in the role in which complex rearrangements in these repetitive regions can influence phenotype, including drug resistance. We have also worked on using circulating tumour DNA to non-invasively characterise copy number variation in primary tumours.

Image 1: Phylogeny of Mycobacterium tuberculosis strains in Papua New Guinea showing estimated dates of acquisition of drug resistance mutations.

Image 2: Depth of coverage of transcripts in SARS-Cov2 revealed by long read nanopore sequencing.


Professor Lachlan Coin, Group leader

Dr Miranda Pitt, Research Officer

Dr Fuyi Li, Research Officer

Dr Eike Steinig, Research Officer

Jessie Chang, PhD Student

Daniel Rawlinson, PhD Student


Professor Tim Stinear, Department of Microbiology and Immunology, The University of Melbourne

Professor Deborah Williamson, Department of Microbiology and Immunology, The University of Melbourne

Professor Fred Hollande, The University of Melbourne Centre for Cancer Research

Professor Matt Cooper, University of Queensland

Associate Professor Mark Blaskovich, University of Queensland

Associate Professor Luregn Schlapbach, University of Queensland

Dr Seweryn Bialasiewicz, University of Queensland

Dr Claire Wainwright, University of Queensland

Professor Mike Levin, Imperial College London

Dr Myrsini Kaforou, Imperial College London

Dr Ulrich Van Both, Ludwig Maximilian University of Munich

Research Opportunities

This research project is available to PhD students, Masters by Research, Honours students, Post Doctor Researchers to join as part of their thesis.
Please contact the Research Group Leader to discuss your options.

Research Outcomes

Brian Eley, Lachlan Coin, Michael Levin, Suzanne Anderson, Method of detecting active tuberculosis in children in the presence of a co-morbidity, WO2014067943A1

Research Publications

Teng, H., Cao, M. D., Hall, M. B., Duarte, T., Wang, S., & Coin, L. J. (2018). Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning. GigaScience, 7(5), giy037.

Zhou, C., Olukolu, B., Gemenet, D. C., Wu, S., Gruneberg, W., Cao, M. D., ... & Coin, L. J. (2020). Assembly of whole-chromosome pseudomolecules for polyploid plant genomes using outbred mapping populations. Nature Genetics, 52(11), 1256- 1264.

Chang, J. J. Y., Rawlinson, D., Pitt, M. E., Taiaroa, G., Gleeson, J., Zhou, C., ... & Coin, L. J. (2021). Transcriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection. Cell Reports, 35(6), 109108.

Nguyen, S. H., Cao, M. D., & Coin, L. J. (2021). Real-time resolution of short-read assembly graph using ONT long reads. PLOS Computational Biology, 17(1), e1008586.

Cao, M. D., Nguyen, S. H., Ganesamoorthy, D., Elliott, A. G., Cooper, M. A., & Coin, L. J. (2017). Scaffolding and completing genome assemblies in real-time with nanopore sequencing. Nature communications, 8(1), 1-10.

Pitt, M. E., Elliott, A. G., Cao, M. D., Ganesamoorthy, D., Karaiskos, I., Giamarellou, H., ... & Coin, L. J. (2018). Multifactorial chromosomal variants regulate polymyxin resistance in extensively drug-resistant Klebsiella pneumoniae. Microbial genomics, 4(3).

Bainomugisa, A., Duarte, T., Lavu, E., Pandey, S., Coulter, C., Marais, B. J., & Coin, L. M. (2018). A complete high-quality MinION nanopore assembly of an extensively drug-resistant Mycobacterium tuberculosis Beijing lineage strain identifies novel variation in repetitive PE/PPE gene regions. Microbial genomics, 4(7).

Research Projects

For project inquiries, contact our research group head.

Faculty Research Themes

Infection and Immunology

School Research Themes

Infection & Immunity, Molecular Mechanisms of Disease

Key Contact

For further information about this research, please contact Head of Laboratory Professor Lachlan Coin

Department / Centre

Microbiology and Immunology

Unit / Centre

Coin Laboratory: Genomics and bioinformatics in infectious disease and cancer

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