WORKSHOP: Machine learning in the life sciences
This record includes training materials associated with the Australian BioCommons workshop ‘Machine Learning in the Life Sciences’. This on 11 June 2024.
Event description
Machine learning promises to revolutionise life science research by speeding up data analysis, enabling prediction of biological patterns and modelling complex biological systems.
But what exactly is machine learning and when should you use it?
This hands-on online workshop provides a high-level introduction to machine learning: what it is, its advantages and disadvantages compared to traditional modelling approaches and the types of scenarios where it may be the right tool for the job. Using example datasets and basic machine learning pipelines we contrast a few commonly used algorithms for constructing predictive models and explore some of their trade-offs. We discuss common pitfalls in how machine learning is applied and evaluated, with a focus on its application in the life sciences, to help you recognise overly optimistic results. We discuss how and why such errors arise and strategies to avoid them.
Lead trainer:
Dr Benjamin Goudey, Research Fellow, Florey Department of Neuroscience and Mental Health
Facilitators:
Dr Erin Graham, Queensland Cyber Infrastructure Foundation (QCIF) / James Cook University
William Pinzon Perez, Queensland Cyber Infrastructure Foundation (QCIF)
Dr Giorgia Mori, Sydney Informatics Hub, University of Sydney
Joseph McConnell, University of Adelaide
Jessica Chung, Melbourne Bioinformatics 0000-0002-0627-0955
Host:
Dr Melissa Burke, Australian BioCommons.
Training materials
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.
Schedule (PDF): Schedule describing the timing of sessions for the in person and online events
Materials shared elsewhere:
This workshop follows the Google Colab Notebook developed by Dr Benjamin Goudey: https://github.com/bwgoudey/IntroMLforLifeScienceWorkshopR
DOI: 10.5281/zenodo.14676360
Licence: Creative Commons Attribution 4.0
Contact: Melissa Burke (melissa@biocommons.org.au)
Keywords: Bioinformatics, Life Science, Machine Learning
Additional information
Status: Active
Authors: Goudey, Benjamin (orcid: 0000-0002-2318-985X), Graham, Erin, Pinzon Perez, William, Mori, Giorgia (orcid: 0000-0003-3469-5632), McConnell, Joseph, Chung, Jessica (orcid: 0000-0002-0627-0955), Mather, Marius
WORKSHOP: Machine learning in the life sciences
https://zenodo.org/records/14676360
https://dresa.org.au/materials/workshop-machine-learning-in-the-life-sciences
This record includes training materials associated with the Australian BioCommons workshop ‘Machine Learning in the Life Sciences’. This on 11 June 2024.
Event description
Machine learning promises to revolutionise life science research by speeding up data analysis, enabling prediction of biological patterns and modelling complex biological systems.
But what exactly is machine learning and when should you use it?
This hands-on online workshop provides a high-level introduction to machine learning: what it is, its advantages and disadvantages compared to traditional modelling approaches and the types of scenarios where it may be the right tool for the job. Using example datasets and basic machine learning pipelines we contrast a few commonly used algorithms for constructing predictive models and explore some of their trade-offs. We discuss common pitfalls in how machine learning is applied and evaluated, with a focus on its application in the life sciences, to help you recognise overly optimistic results. We discuss how and why such errors arise and strategies to avoid them.
Lead trainer:
Dr Benjamin Goudey, Research Fellow, Florey Department of Neuroscience and Mental Health
Facilitators:
Dr Erin Graham, Queensland Cyber Infrastructure Foundation (QCIF) / James Cook University
William Pinzon Perez, Queensland Cyber Infrastructure Foundation (QCIF)
Dr Giorgia Mori, Sydney Informatics Hub, University of Sydney
Joseph McConnell, University of Adelaide
Jessica Chung, Melbourne Bioinformatics 0000-0002-0627-0955
Host:
Dr Melissa Burke, Australian BioCommons.
Training materials
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.
Schedule (PDF): Schedule describing the timing of sessions for the in person and online events
Materials shared elsewhere:
This workshop follows the Google Colab Notebook developed by Dr Benjamin Goudey: https://github.com/bwgoudey/IntroMLforLifeScienceWorkshopR
Melissa Burke (melissa@biocommons.org.au)
Goudey, Benjamin (orcid: 0000-0002-2318-985X)
Graham, Erin
Pinzon Perez, William
Mori, Giorgia (orcid: 0000-0003-3469-5632)
McConnell, Joseph
Chung, Jessica (orcid: 0000-0002-0627-0955)
Mather, Marius
Bioinformatics, Life Science, Machine Learning