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ZENODO
Other ORP type . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Other ORP type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other ORP type . 2026
License: CC BY
Data sources: Datacite
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WEBINAR: Future of AI in Life Sciences

Authors: Huynh, Minh; Goudey, Benjamin;

WEBINAR: Future of AI in Life Sciences

Abstract

This record includes training materials associated with the Australian BioCommons webinar 'Future of AI in Life Sciences'. This webinar took place on 29 April 2026. Webinar Description Artificial intelligence (AI) and machine learning (ML) are rapidly changing the way we work in the life sciences. Recently, Australian BioCommons called upon the community to share how they apply these technologies to molecular data analysis to help map future needs. Join us for this dedicated webinar where we will share a summary of the findings from our national consultation. This session will explore the general survey results, highlighting the national trends, bottlenecks, and digital infrastructure gaps you've helped identify. It will also include a ‘first look’ at our initial training program, giving you a sneak peek into the workshops and resources we’ll be launching later this year to better support the application of AI in life science research. Speakers: Dr Minh Huynh, AI in Research Training Lead, Australian BioCommons and Sydney Informatics Hub; Dr Benjamin Goudey, AI Technical Lead, Australian BioCommons Host: 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: Future of AI in Life Sciences Zenodo - Event metadata - webinars.pdf: Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Future of AI in Life Sciences Webinar.pdf: slides presented during the webinar. Files and materials shared elsewhere: Recording of the presentation on the Australian BioCommons YouTube channel: https://youtu.be/yPBuHT1zagI

Related Organizations
Keywords

Machine Learning, Artificial Intelligence, Life Sciences

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average