Add abacbs workshop

Author: tlitfin

_data/CONTRIBUTORS.yml

@@ -144,4 +144,13 @@ Begoña Heras:
 Fiona Whelan:
     affiliation: Group Leader in Biotechnology, Adelaide University
     git: fionawhelan
-    orcid: 0000-0002-0791-6850
+    orcid: 0000-0002-0791-6850
+
+Georgie Samaha:
+    affiliation: Bioinformatics Group Lead, Sydney Informatics Hub, University of Sydney
+    git: georgiesamaha
+    orcid: 0000-0003-0419-1476
+
+Farah Zaib Khan:
+    affiliation: Scientific Business Analyst, The University of Melbourne, Australian BioCommons
+    orcid: 0000-0002-6337-3037

pages/activities/abacbs_workshop.md

@@ -0,0 +1,23 @@
+---
+title: ABACBS 2025 workshop
+description: Leveraging peak Australian compute to enable workflows for predictive structural biology at scale
+type: activity_in_progress
+roadmap: A computational structural biology training program (Roadmap D2)
+roadmap_category: D2
+contributors: [Johan Gustafsson, Ziad Al-Bkhetan, Thomas Litfin, Sarah Beecroft, Georgie Samaha, Mitchell O'Brien, Farah Zaib Khan]
+toc: false
+redirect_from: /website/abacbs25_workshop
+---
+ 
+## Details
+ 
+Community members will present a [workshop](https://blackochrelabs.au/abacbs2025_workshops/) at the [ABACBS conference](https://www.abacbs.org/abacbs2025) in Adelaide describing structural biology workflows on national HPC infrastructure.
+ 
+### Abstract
+ 
+Deep learning for structural biology has numerous applications, ranging from basic research through to clinical application. A key challenge with these approaches is accessibility, and much work is currently being conducted to develop computational workflows to improve this access. However, building, executing, and sharing workflows is challenging. The difficulty only increases when implementing novel approaches like deep learning, and even more so when moving these workflows to national infrastructure to operate at scale. Some of the challenges include knowing how to develop a workflow to optimise use of these large compute systems, how to configure and deploy workflows that can efficiently employ both CPU and GPU, and how to share the workflows created so that others can find, understand, reuse, and ultimately cite the workflow. This workshop will examine these challenges from the perspective of a workflow’s life cycle, and in doing so provide both theory and hands-on activities that will support bioinformaticians to develop, execute, and share computational workflows for structural biology at scale.
+ 
+### Content
+ 
+- Presentation Slides coming soon
+- Workshop content coming soon