Al Bkhetan Z3, Mok 3, Manos S3, Mather M1, Michie K1, O'Brien M3, Vu M1, Zhu A1,3, Phan A1,3, Litfin T2,3
1University of Sydney, Sydney, Australia, 2University of New South Wales, Sydney, Australia, 3Australian BioCommons, Melbourne, Australia
Biography:
Thomas Litfin is a Senior Research Associate at the University of New South Wales working in the Structural Biology Facility of the Mark Wainwright Analytical Center. He completed his PhD in structural bioinformatics from Griffith University in 2020 and has published over 30 articles relating to computational methods in structural biology.
Anne Phan is a Software Developer contributing to the Structural Biology Platform at the Sydney Informatics Hub and Australian BioCommons. She has a background in biotechnology and holds a Master of Computer Science from the University of Sydney. Her interdisciplinary training allows her to bridge biological research and software development in scientific projects.
Abstract:
AI-based protein structure prediction and design are emerging as powerful tools for modern life science, but the software can be expensive and difficult to access, configure and operate. This presentation focuses on the Australian BioCommons Structural Biology Platform (SBP), a research software solution that turns AI-enabled structural biology workflows into accessible, managed services for Australian researchers.
The platform acts as a software layer between complex computational methods and users. It provides web interfaces for submitting analyses, tracking jobs, viewing reports and downloading results, eliminating the need to manage software dependencies, infrastructure or data. Using Australian BioCommons Access as the authentication and access provider, users can sign in and seamlessly access Australian life science services, including Galaxy Australia and the Bioplatforms Australia Data Portal.
The SBP-administered credit and quota management system abstracts away the billing complexity of workloads with highly heterogeneous resource requirements. Within the platform, administrators can allocate sponsored compute credits and monitor user quotas, supporting fair and sustainable access to shared resources across research communities.
The SBP backend currently runs on National Computational Infrastructure (NCI) systems but is designed so that compute backends can be changed as requirements, partnerships with compute service providers and infrastructure evolve. The project aims to leverage flexible infrastructure capacity to transform demanding computational methods into national scientific capabilities. The platform is highly extensible via direct integration of Nextflow workflows from community contributions and global registries such as nf-core.
Our presentation will include a live demonstration of the platform, with a walkthrough of the user experience and key software and technical components. SBP’s value lies in the software patterns around the models: accessible interfaces, shared identity, reproducible execution, backend flexibility, credit-based governance, reporting and support for Australian life science and industry translation pathways.
