update infrastructure roadmap

_includes/events.html

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         .events-list {
             display: grid;
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_includes/section-navigation-tiles_mod.html

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_includes/tiles-simple.html

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index.md

@@ -8,6 +8,8 @@ toc: false
 tiles:
   - title: "Join the conversation"
     url: /join_conversation
+  - title: "Read the Australian infrastructure roadmap"
+    url: https://doi.org/10.5281/zenodo.15786982
 ---
 
 

pages/activities/infrastructure_roadmap.md

@@ -1,15 +1,65 @@
 ---
 title: Infrastructure Roadmap
 description: Draft and publish an Australian infrastructure roadmap for addressing computational challenges facing structural biology.
-type: activity_in_progress
+type: activity_completed
 roadmap: Community co-authored document
 roadmap_category: none
 toc: false
 ---
 
-## Details
+## Citation
+
+> Michie, K. A., Litfin, T., Beecroft, S. J., Collins, B., Czabotar, P., Downton, M., Doyle, M. T., Ghosal, D., Grinter, R., Knott, G. J., Samaha, G., Christiansen, J. H., & Gustafsson, O. J. R. (2025). Australian Structural Biology Deep-Learning Infrastructure Roadmap. Zenodo. [https://doi.org/10.5281/zenodo.15786982](https://doi.org/10.5281/zenodo.15786982)
+
+
+## Executive Summary from roadmap
+
+Enabled by advances in deep learning methods for protein structure prediction and de novo protein
+design, computational structural biology has rapidly emerged as a powerful technology driving innovation
+in both fundamental and translational science. The technology underpins breakthroughs in drug design,
+diagnostics, personalised medicine, and synthetic biology. However, effective use requires concentrated
+interdisciplinary expertise and access to modern graphics processing unit (GPU) hardware that few
+Australian researchers or industry can sustain.
+The Australian structural biology community has taken a collaborative approach to develop this
+infrastructure roadmap which describes the existing national landscape, identifies and prioritizes critical
+research bottlenecks, and proposes a national strategy to unlock the immense potential of computational
+structural biology for Australian researchers. This strategy is intended to evolve as the requirements of
+the community change. The roadmap outlines the challenges faced but also presents opportunities to
+maximize the value of this new technology. A robust, sovereign capability in computational structural
+biology and protein design will position Australian universities, research institutes, and industry at the
+forefront of global innovation.
+
+The community roadmap outlines 4 major deliverables including:
+
+- **D1. A dedicated community space** to foster collaboration and share best-practice
+recommendations for software deployments, benchmarking, validations and insights developed
+within the community.
+- **D2. Community training resources** to on-board diverse stakeholders within the context of
+computational structural biology and strengthen the national impact of community expertise.
+- **D3. National computational infrastructure** built on increased hardware investment and a
+user platform to facilitate efficient, high-throughput utilization of national computing resources
+and drive translational outcomes enabled by curated and validated computational structural
+biology technologies.
+- **D4. Alignment, integration and engagement with global best-practice efforts** for
+computational structural biology infrastructure and research.
+
+Achieving these outcomes will not only enable the community to add value across diverse research
+disciplines within Australia, but will drive innovation and enhance the national research and enterprise
+profile in medicine and biotechnology on the global stage.
+
+
+{% include image.html file="/activities/Computational Structural Biology Roadmap.png" caption="Roadmap Figure 3. Proposed infrastructure to support Australian structural biology computation: (D1) Australian Structural
+Biology community space. (D2) Tailored training program connects the proposed infrastructure to the
+BioCommons training program and includes community generated guidance material. (D3) Shared platform, or
+platforms, for computational structural biology. Protein sequences, or other relevant sequence data (e.g.
+nucleotide), as well as code, are inputs into the envisaged hypothetical shared platform for computational
+structural biology analyses, which provides both command-line interface (CLI) or graphical user interface
+(GUI)-based access to validated software tools and workflows. This system is underpinned by sufficient and
+appropriate computational infrastructure. (D4) Alignment to international best practice highlights the aim to align,
+adopt and collaborate with international peer infrastructures to deliver the proposed infrastructure. Arrows
+indicate the general flow of data. See Appendix 1 for a list of open source tools / workflows that may be
+included in D3. Globe image: Clker-Free-Vector-Images, CC0, via Wikimedia Commons." alt="Roadmap Figure 3" max-width="10" %}
 
-The infrastructure roadmap document describes the existing national landscape, identifies and prioritizes critical research bottlenecks, and proposes a national strategy to unlock the immense potential of computational structural biology for Australian researchers.
 
 ### Completed
 
@@ -18,15 +68,10 @@ The infrastructure roadmap document describes the existing national landscape, i
 - Review and updates based on feedback from co-authors and academic panel.
 - Review and updates based on feedback from community and BioCommons infrastructure partners.
 - Review and updates based on feedback from international experts.
-
-### In Progress
-
 - Addressing final review comments.
-
-### Future
-
 - Publication to Zenodo.
 
+
 ### Contributors
 
 - Australian Structural Biology Computing Community