FAIR Data Standards and AI, Methods and Training in Bioinformatics
BIO390 UZH HS26 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y-03G-85
Geert van Geest (UB & SIB)
The life sciences domain thrives on shared data. From reference databases to community-curated knowledgebases, the field’s progress rests on data that are open and FAIR: findable, accessible, interoperable and reusable. This lecture starts from that foundation, drawing on resources developed at the SIB Swiss Institute of Bioinformatics, and explores why FAIR principles matter more than ever now that AI models depend on large volumes of well-annotated, machine-actionable data.
This goes beyond data: the analyses built on them must also be reproducible and reusable. We will discuss how reproducible workflows impact progression in science. At the same time, AI is rapidly changing how bioinformaticians write code, explore data and interpret results, bringing new opportunities but also new risks to rigour and understanding. We close by reflecting on the skills a bioinformatician needs in this ever-evolving landscape, and on how training can help researchers to perform solid and innovative bioinformatics analyses.