Cancer Bioinformatics | Professor Lachlan Coin

Professor Lachlan Coin's Cancer Bioinformatics group develops genomic and transcriptomic tools to develop biomarkers for rapid characterisation of disease state and prediction of drug susceptibility, with the aim of decreasing the time taken from hospital admission to administering the right treatment. The group also develops biomarkers for measuring treatment response, with a focus on infectious disease and cancer.

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

Much of the group's current research utilises 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. They have emerging interests in single-cell long-read RNA and DNA sequencing, particularly as they relate to improving diagnostic and prognostic tools.