How to manage biological data and use computational methods to power life science research
Start date: 27 September 2022
End date: 29 September 2022
Time: 09.00 – 17.00
Venue: Online (via Zoom)
Enquiries: [email protected]
Registration deadline: 26 September 2022
Modern life science research is increasingly reliant on data science, and a failure to keep pace with computational methods will leave UK life science research treading water.
In partnership with ELIXIR-UK, the UK-CBCB conference will cover the breadth of biological data management, analysis and sharing.
This three-day event will combine a keynote lecture with presentations of use cases from researchers working at the cutting edge, plus breakout discussion groups where participants can exchange expertise and challenges with one another, working to provide multidisciplinary solutions to complex problems together.
In order to maximise engagement across multiple disciplines in this online event, we have opted for a streamlined programme (no parallel sessions), short introductory talks and targeted breakout discussion groups to focus on particular challenges underpinned by a biological question. There will be numerous breakout discussions in each themed session, based upon the flash presentations from our research facilitators.
The confirmed themes for this event are:
- Bioimaging and Artificial Intelligence
- Structural Bioinformatics
- Metagenomics and Microbial Bioinformatics
- Spatial Transcriptomics
- Federated Analytics/Learning
- Open Science
- Sex and Gender Bias in Computational Disciplines
Who is this event for?
UK-CBCB is designed to bring together researchers from a range of research backgrounds to explore and discuss challenges faced at the very cutting edge of research in these fields.
We want this year’s event to be as engaging and openly accessible as possible, so we expect a broad range of topics to be introduced for novices but with cutting-edge case studies to attract even the most experienced researchers. Therefore we welcome all researchers across the spectrum of career points from postgraduate students to professors and those managing resources and infrastructures.
We particularly encourage early career researchers and PhD students to attend in order to gain exposure to the breadth of computational approaches in data-intensive bioscience with ample opportunity to hear from experts working at the cutting edge as well as those making tentative steps into the fields of discussion to learn of the challenges faced when entering the field.