What is the workshop about?
Recent developments in the field of Artificial Intelligence (AI) and machine learning (ML) are transforming many aspects of technology and engineering. This workshop will explore how such approaches could be used in biological research.
Machine Learning has a long tradition in biology with some notable successes, in particular in the area of bioinformatics, e.g. neural networks were employed in the early 90’s for protein secondary structure prediction, outcompeting existing methods. Many current tools in bioinformatics (sequence analysis, motif prediction, function prediction, network inference, etc.) and computational biology (image segmentation, systems identification, data visualisation, etc.) use AI and ML approaches.
New developments in deep learning are seen as step-changing and may allow for applications that go well beyond the traditional use of such tools in biology.
Biological sciences are becoming increasingly data-rich and new approaches are required for analysing and making sense of this data. For instance, challenges such as predictive breeding for different climates will require the integration of huge amounts of data from various ‘omics technologies. AI and ML offer a set of attractive tools for dealing with the complexity and amount of data from areas such as high-throughput sequencing, proteomics, metabolomics, crop phenotyping and imaging.
This workshop is thus very timely and will generate an open forum for discussing these developments, focussing on key challenges that will benefit from AI approaches. It will make links between the institutes, relevant academics and other stakeholders. It is expected that the workshop will lead to joint proposals and studentship applications in AI and ML on these exciting new technological innovations to push forward challenging areas of biology relevant for BBSRC’s strategic vision.
This workshop is a collaborative effort from Richard Morris (John Innes Centre), Federica Di Palma (Earlham Institute) and Chris Rawlings (Rothamsted Research) and is supported by funds from the BBSRC.
Target audience
Researchers who are looking to or who are already applying AI and ML approaches to their work and who are based at the BBSRC strategically-funded research institutions. Invitations will be extended to relevant funding agencies and from industry as appropriate. Answers given to the online registration questions will be used to select attendees. The total number of spaces available for this are limited to 40.
Researchers from all career stages are invited to attend the open lectures during the morning part of the workshop and offered on a first-come first served basis through the registration link. Researchers not selected from their applications will be eligible to attend these open lectures also.
