WEBINAR: Getting started with command line bioinformatics
This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021.
Bioinformatics skills are in demand like never before and biologists are stepping up to the challenge of...
Keywords: Bioinformatics, Command line, Workflows, Bash, Computational biology
WEBINAR: Getting started with command line bioinformatics
https://zenodo.org/records/5068997
https://dresa.org.au/materials/webinar-getting-started-with-command-line-bioinformatics-248027d1-0773-485a-b511-831e2fd4cc64
This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021.
Bioinformatics skills are in demand like never before and biologists are stepping up to the challenge of learning to analyse large and ever growing datasets. Learning how to use the command line can open up many options for data analysis but getting started can be a little daunting for those without a background in computer science.
Parice Brandies and Carolyn Hogg have recently put together ten simple rules for getting started with command-line bioinformatics to help biologists begin their computational journeys. In this webinar Parice walks you through their hints and tips for getting started with the command line. She covers topics like learning tech speak, evaluating your data and workflows, assessing computational requirements, computing options, the basics of software installation, curating and testing scripts, a bit of bash and keeping good records. The webinar will be followed by a short Q&A session.
The slides were created by Parice Brandies and are based on the publication ‘Ten simple rules for getting started with command-line bioinformatics’ (https://doi.org/10.1371/journal.pcbi.1008645). The slides are shared under a Creative Commons Attribution 4.0 International unless otherwise specified and were current at the time of the webinar.
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.
Getting started with command line bioinformatics - slides (PDF): Slides presented during the webinar
Materials shared elsewhere:
A recording of the webinar is available on the Australian BioCommons YouTube Channel
https://youtu.be/p7pA4OLB2X4
Melissa Burke (melissa@biocommons.org.au)
Brandies, Parice (orcid: 0000-0003-1702-2938)
Hogg, Carolyn (type: Supervisor)
Bioinformatics, Command line, Workflows, Bash, Computational biology
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