2026-08-14 –, Room 5
Round table discussion on using Julia for computational biology: Use cases, limitations and concerns we should address, and where to focus our collective efforts.
Julia is especially well suited for computational biology, and BioJulia was one of the earliest Julia organizations. Due to the decentralized and ad hoc nature of Julia communities, we rarely have a chance to reflect and take stock of how the organization is doing, and whether we are serving our users and our own research needs to the best of our ability.
In this Birds of Feather, we want to hear from users and developers about how and why they use Julia for computational biology, or what problems prevent them from doing so. We welcome feedback on the BioJulia organization, the ecosystem of Julia for computational biology, and the state of relevant packages.
Although no one has the authority to delegate developer efforts, we encourage discussion about whether our collective programming effort is well spent, and how BioJulia and other Julia organizations can improve to better serve our users.
This discussion is for everyone interested in Julia for computational biology; whether you are a BioJulia developer, a Julia developer in another field interested in biology, or someone interested in what Julia can bring to biology.
I am a research software engineer from Copenhagen, Denmark.
I currently work for the Danish health authorities, writing software for pathogen surveillance. I am trained as a molecular biologist, and have previously been working as an academic researching bioinformatics.
I program in Python, Rust and Julia, and am an active developer in the BioJulia ecosystem. I write Julia packages for efficient I/O and parsing, and foundational bioinformatics functionality such as BioSequences and Kmers.jl.