Justin Bedő

I am a researcher at the Walter and Eliza Hall institute in the Papenfuss lab and an honorary fellow in the School of Computing and Information Systems at the University of Melbourne. I work on machine learning and am interested in developing techniques for knowledge discovery in biological data. In particular, I'm interested in precision medicine.



Git repositories

Machine learning methods for somatic genome rearrangement detection

Structural variants (SVs) are large-scale genomic changes and are an important type of mutation in cancer. SVs can occur through a variety of biological mechanisms leading to insertions, deletions, duplications, inversions, and translocations in the genome. These mutations can cause cancers and affect response to therapy. A student project is available to develop machine learning methods that generate the best possible results from whole genome tumour-normal sequencing data for each patient.

Papenfuss lab student projects


BioNix is a tool for reproducible bioinformatics that unifies workflow engines, package managers, and containers. It is implemented as a lightweight library on top of the Nix deployment system. BioNix is currently in use at WEHI and is actively developed.

Git repository

svaRetro & svaNUMT

svaRetro and svaNUMT are R packages for detecting retrotransposed transcripts and mitocondrial insertions into the nuclear genome (NUMT) from structural variant calls.


Recent publications

Google Scholar


GPG key
Matrix (@jb:vk3.wtf)
ORCID iD: 0000-0001-5704-0212

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