Accelerating deep learning in Australian structural biology research

Enabled by rapid advances in deep learning methods for protein structure prediction, computational structural biology is driving major innovations in life sciences research. However, making effective use of these technologies requires cutting-edge software, highly specialised hardware, and interdisciplinary expertise.

To tackle these challenges, a passionate group of researchers officially formed the Australian Structural Biology Computing (ASBC) community in early 2025. Supported by BioCommons, this community-led initiative set out to share computational knowledge, methods and resources. Less than a year later, we can already see the value they bring to the Australian research sector.

How has the ASBC community grown?

Since its formation, the community has been moving quickly to address the needs identified in the Australian Structural Biology Deep-Learning Infrastructure Roadmap. The roadmap has already demonstrated its value to the sector, having been viewed over 1,100 times and downloaded over 900 times, in addition to being used in funding applications and publications

To further connect researchers, BioCommons assisted in the development of a new Community Platform website that is now live, serving as a virtual hub for all users in Australia, with new resources and opportunities for contributions being added to the platform over time.

What training and resources are now available?

Capacity building has been a key focus for the ASBC community, and they have been integral to several key activities in 2025:

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