WEBINAR: KBase - A knowledge base for systems biology
This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.
Event description
Developed for bench biologists and bioinformaticians, The Department of Energy Systems...
Keywords: Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
WEBINAR: KBase - A knowledge base for systems biology
https://zenodo.org/records/5717580
https://dresa.org.au/materials/webinar-kbase-a-knowledge-base-for-systems-biology-653d9753-989d-4194-9230-6e2d90652955
This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.
Event description
Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a free, open source, software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function.
This webinar will provide an overview of the KBase mission and user community, as well as a tour of the online platform and basic functionality. You’ll learn how KBase can support your research: Upload data, run analysis tools (Apps), share your analysis with collaborators, and publish your data and reproducible workflows. We’ll highlight a brand new feature that enables users to link environment and measurement data to sequencing data. You’ll also find out how KBase supports findable, accessible, interoperable, and reusable (FAIR) research by providing open, reproducible, shareable bioinformatics workflows.
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.
Q&A for Australian BioCommons KBase Webinar [PDF]: Document containing answers to questions asked during the webinar and links to additional resources
Introduction to KBase: Australian BioCommons Webinar [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/tJ94i9gOJfU
The slides are also available as Google slides:
https://tinyurl.com/KBase-webinar-slides
Melissa Burke (melissa@biocommons.org.au)
Dow, Ellen (orcid: 0000-0002-2079-0260)
Wood-Charlson, Elisha (orcid: 0000-0001-9557-7715)
Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
WORKSHOP: R: fundamental skills for biologists
This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.
Event description
Biologists need data analysis skills to be able to...
Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WORKSHOP: R: fundamental skills for biologists
https://zenodo.org/records/6766951
https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists-81aa00db-63ad-4962-a7ac-b885bf9f676b
This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.
Event description
Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.
R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.
Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R.
Topics covered in this workshop include:
Spreadsheets, organising data and first steps with R
Manipulating and analysing data with dplyr
Data visualisation
Summarized experiments and getting started with Bioconductor
This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative.
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.
Schedule (PDF): A breakdown of the topics and timings for the workshop
Recommended resources (PDF): A list of resources recommended by trainers and participants
Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel.
Materials shared elsewhere:
This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available.
https://saskiafreytag.github.io/biocommons-r-intro/
This is derived from material produced as part of The Carpentries Incubator project
https://carpentries-incubator.github.io/bioc-intro/
Melissa Burke (melissa@biocommons.org.au)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Doyle, Maria
Ansell, Brendan (orcid: 0000-0003-0297-897X)
Varshney, Akriti
Bourke, Caitlin (orcid: 0000-0002-4466-6563)
Conradsen, Cara (orcid: 0000-0001-9797-3412)
Jung, Chol-Hee (orcid: 0000-0002-2992-3162)
Sandoval, Claudia
Chandrananda, Dineika (orcid: 0000-0002-8834-9500)
Zhang, Eden (orcid: 0000-0003-0294-3734)
Rosello, Fernando (orcid: 0000-0003-3885-8777)
Iacono, Giulia (orcid: 0000-0002-1527-0754)
Tarasova, Ilariya (orcid: 0000-0002-0895-9385)
Chung, Jessica (orcid: 0000-0002-0627-0955)
Moffet, Joel
Gustafsson, Johan (orcid: 0000-0002-2977-5032)
Ding, Ke
Feher, Kristen
Perlaza-Jimenez, Laura (orcid: 0000-0002-8511-1134)
Crowe, Mark (orcid: 0000-0002-9514-2487)
Ma, Mengyao
Kandhari, Nitika (orcid: 0000-0002-0261-727X)
Williams, Sarah
Nelson, Tiffanie (orcid: 0000-0002-5341-312X)
Schreiber, Veronika (orcid: 0000-0001-6088-7828)
Pinzon Perez, William
Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
23 (research data) Things
23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:
- Getting started
- Learn more
- Challenge me
All resources used in the program are online...
Keywords: research data management, training material
23 (research data) Things
https://zenodo.org/records/3955524
https://dresa.org.au/materials/23-research-data-things-793872d2-c221-4cd6-91be-11a313c74b78
23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:
* Getting started
* Learn more
* Challenge me
All resources used in the program are online and free to use and reuse under a Creative Commons Attribution 4.0 International licence. You could use all of them as a self-paced course, or choose components to integrate into your own course.
The 23 things are designed to build knowledge as the program progresses, so if you’re new to the world of research data management, we suggest you start with things 1-3 and then decide where you want to go from there.
These materials supported an international community-based training program delivered in 2016 by the Australian National Data Service.
This release migrates these materials to a GitHub repository for continued maintenance. Some updates were made to material that was outdated.
We welcome contributions and suggestions via GitHub Issue or Pull Request.
contact@ardc.edu.au
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Stokes, Liz (orcid: 0000-0002-2973-5647)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Kelly, Andrew (orcid: 0000-0002-5377-5526)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Levett, Kerry (orcid: 0000-0001-5963-0195)
Brady, Catherine (orcid: 0000-0002-7919-7592)
research data management, training material
ARDC FAIR Data 101 self-guided
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the...
Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
ARDC FAIR Data 101 self-guided
https://zenodo.org/records/5094034
https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub.
contact@ardc.edu.au
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Martinez, Paula A. (orcid: 0000-0002-8990-1985)
Simons, Natasha (orcid: 0000-0003-0635-1998)
Russell, Keith (orcid: 0000-0001-5390-2719)
McCafferty, Siobhann (orcid: 0000-0002-2491-0995)
Ferrers, Richard (orcid: 0000-0002-2923-9889)
McEachern, Steve (orcid: 0000-0001-7848-4912)
Barlow, Melanie (orcid: 0000-0002-3956-5784)
Brady, Catherine (orcid: 0000-0002-7919-7592)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Quiroga, Maria del Mar (orcid: 0000-0002-8943-2808)
training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
ARDC Guide to making software citable
A short guide to making software citable using a code repository, an ORCID and a licence.
Keywords: Software citation, Software publishing, Software registries, Software repositories, Research software, training material
ARDC Guide to making software citable
https://zenodo.org/records/5003989
https://dresa.org.au/materials/ardc-guide-to-making-software-citable-46d0f9e4-ef55-43b9-b237-3e52a9d1e141
A short guide to making software citable using a code repository, an ORCID and a licence.
contact@ardc.edu.au
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Martinez, Paula Andrea (type: ProjectLeader)
Software citation, Software publishing, Software registries, Software repositories, Research software, training material