WEBINAR: Where to go when your bioinformatics outgrows your compute
This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.
Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute...
Keywords: Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing
WEBINAR: Where to go when your bioinformatics outgrows your compute
https://zenodo.org/records/5240578
https://dresa.org.au/materials/webinar-where-to-go-when-your-bioinformatics-outgrows-your-compute-7a5a0ff8-8f4f-4fd0-af20-a88d515a6554
This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.
Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute resources. “I don’t know what compute resources I will need”, “My analysis won’t run and I don’t know why” and "Just getting it to work" are common pain points for researchers. In this webinar, you will learn how to understand the compute requirements for your bioinformatics workflows. You will also hear about ways of accessing compute that suits your needs as an Australian researcher, including Galaxy Australia, cloud and high-performance computing services offered by the Australian Research Data Commons, the National Compute Infrastructure (NCI) and Pawsey. We also describe bioinformatics and computing support services available to Australian researchers.
This webinar was jointly organised with the Sydney Informatics Hub at the University of Sydney.
Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.
Files and materials included in this record:
Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.
Where to go when your bioinformatics outgrows your compute - slides (PDF and PPTX): Slides presented during the webinar
Australian research computing resources cheat sheet (PDF): A list of resources and useful links mentioned during the webinar.
Materials shared elsewhere:
A recording of the webinar is available on the Australian BioCommons YouTube Channel:
https://youtu.be/hNTbngSc-W0
Melissa Burke (melissa@biocommons.org.au)
Samaha, Georgina (orcid: 0000-0003-0419-1476)
Chew, Tracy (orcid: 0000-0001-9529-7705)
Sadsad, Rosemarie (orcid: 0000-0003-2488-953X)
Coddington, Paul (orcid: 0000-0003-1336-9686)
Gladman, Simon (orcid: 0000-0002-6100-4385)
Edberg, Roger
Shaikh, Javed
Cytowski, Maciej (orcid: 0000-0002-0007-0979)
Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing
Principles Aligned Institutionally-Contextualised (PAI-C) RDM Training
This GitHub repository contains resources for an institution to contextualise a principles-based RDM training with its institution's research data management policies, processes and systems.
The adoption of PAI-C across institutions will contribute to a common baseline understanding of RDM...
Keywords: PAI-C, Training, Data Management
Principles Aligned Institutionally-Contextualised (PAI-C) RDM Training
https://github.com/Adrian-W-Chew/PAI-C-RDM-Training
https://dresa.org.au/materials/principles-aligned-institutionally-contextualised-pai-c-rdm-training
This GitHub repository contains resources for an institution to contextualise a principles-based RDM training with its institution's research data management policies, processes and systems.
The adoption of PAI-C across institutions will contribute to a common baseline understanding of RDM across institutions, which in turn will facilitate cross institutional management of data (e.g. when researchers move between institutions, and collaborate across institutions).
Dr Adrian W. Chew (w.l.chew@unsw.edu.au)
Dr Adrian W. Chew
Dr Adele Haythornthwaite
Brock Askey
Dr Jacky Cho
Dr Anesh Nair
Dr Kyle Hemming
Iftikhar Hayat
Joanna Dziedzic
Janice Chan
Kaitlyn Houston
Linlin Zhao
Caitlin Savage
Jessica Suna
Dr Emilia Decker
Sharron Stapleton
PAI-C, Training, Data Management