The theory and practice of Oxford Nanopore basecaller model training

Event abstract

Oxford Nanopore basecallers use machine learning to achieve accurate and fast basecalling, provided by models that are the most suitable for the widest range of applications. However, training your own bespoke basecaller for your tailored experiment may provide application-specific benefits. During this Knowledge Exchange, Mike Vella shared where these gains can be made, and how to achieve them for your own projects. Demonstrating this with the open source basecaller Bonito, you can expect to learn:

• The core theory of how Oxford Nanopore basecalling models work
• A practical guide on how to train models using Bonito
• When to and when not to train your own models

Meet the speaker

Mike Vella is a Director of Machine Learning Operations at Oxford Nanopore. He received his Ph.D. in Computational Neuroscience from the University of Cambridge, where he became fascinated with using computers to solve problems in Biology. Mike’s work involves developing practical solutions using machine learning to improve the speed and accuracy of bioinformatics software.