Analysis of cryo electron microscopy data with artificial intelligence
||Analysis of cryo electron microscopy data with artificial intelligence|
||Lukas Grunewald <firstname.lastname@example.org>|
||2023-10-26 – 2024-05-01|
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.
Might use cryoDRGN as well to analyse already obtained cryo-EM data from our group.