Magic algorithms and RNA molecules

Multi-dimensional scaling, unsupervised learning, principal component analysis, RNA folding - have you ever heard these terms? If not, don’t worry! In this lecture, we’ll explore what they mean together, and what plotting dots on graph paper and matching pairs of brackets have to do with predicting the intricate 3D shapes of structured RNA molecules.

In the era of AlphaFold, even AI struggles to crack the mystery of ribonucleic acid, one of the trickiest biological macromolecules. Its sequence is written in just four letters - A, U, G, and C - yet it folds into an astonishing variety of shapes. We’ll discover how computational algorithms help us unravel the nature of RNA, take a look at the building blocks of its 3D structure, and step into the shoes of RNA structure predictors.