Title:	Analysis of cryo electron microscopy data with artificial intelligence
DNr:	Berzelius-2024-202
Project Type:	LiU Berzelius
Principal Investigator:	Lukas Grunewald <lukas.grunewald@kemi.uu.se>
Affiliation:	Uppsala universitet
Duration:	2024-05-14 – 2024-12-01
Classification:	10602
Keywords:

Abstract

Machine learning models can be used to complement experimental data and proved to be a powerful tool to aid to solve and validate structures and dynamics of proteins. By combining machine learning with experimental data, they can prove previously unexplained changes and behavior in proteins. For my project, I would like to use alphafold for protein structure prediction and furthermore, train my own neural network for analysing conformational variability in cryo-electron microscopy and use this information to reconstruct protein ensembles. cryoDRGN will be used as well to analyse and compare our method to it. Our method worked already nicely on synthetic data and now we would like to extend to analyse real experimental data with it.