An Interview with BioLizard & Bridge Informatics CEOs Liesbeth Ceelen & Dan Ryder
An overwhelming amount of data is a nice problem to have, but a hard one to manage well. Dan & Liesbeth talk about the opportunities, unique challenges, and areas for growth at the intersection of biology and data science. Dan, Liesbeth, can you please introduce...
Three best practices for applying machine learning in the life sciences
It has only become easier to apply artificial intelligence (AI) and machine learning (ML) to biological questions – even without a deep knowledge of data science. However, with this great potential, comes some potential pitfalls. In our experience, the most important...
Machine learning for protein engineering and design: Beyond AlphaFold
As you may already know, AlphaFold is a much-hyped tool that applies machine learning to protein structure prediction. But the potential of machine learning for protein engineering and design doesn’t end there! Machine learning can be used to achieve a lot of...
Three reasons why you should use machine learning for protein engineering and design
“Machine Learning”. It’s both a buzz word and an exciting method – but how, and perhaps more importantly why, should you start using machine learning for protein engineering and design? Put simply, AI can transform your data into an...