Difference between revisions of "2020Cossio CrossValidation"
(Created page with "== Citation == Cossio, P. Need for Cross-Validation of Single Particle Cryo-EM. Journal of chemical information and modeling, 2020, 60, 2413-2418 == Abstract == Cross-vali...")
Latest revision as of 07:43, 27 July 2020
Cossio, P. Need for Cross-Validation of Single Particle Cryo-EM. Journal of chemical information and modeling, 2020, 60, 2413-2418
Cross-validation is used to determine the validity of a model on unseen data by assessing if the model is overfitted to noise. It is widely used in many fields, from artificial intelligence to structural biology in X-ray crystallography and nuclear magnetic resonance. Although there are concerns of map overfitting in cryo-electron microscopy (cryo-EM), cross-validation is rarely used. The problem is that establishing a performance metric of the maps over unseen data (given by 2D-projection images) is difficult due to the low signal-to-noise ratios in the individual particles. Here, I present recent advances for cryo-EM map reconstruction. I highlight that the gold-standard procedure can fail to detect map overfitting in certain cases, showing the necessity of assessing the map quality on unbiased data. Finally, I describe the challenges and advantages of developing a robust cross-validation methodology for cryo-EM.