%0 Journal Article
%A Reggiano, Gabriella
%A Lugmayr, Wolfgang
%A Farrell, Daniel
%A Marlovits, Thomas
%A DiMaio, Frank
%T Residue-level error detection in cryoelectron microscopy models
%J Structure
%V 31
%N 7
%@ 0969-2126
%C Cambridge, Mass.
%I Cell Press
%M PUBDB-2023-07781
%P 860-869.e4
%D 2023
%X Building accurate protein models into moderate resolution (3–5 Å) cryoelectron microscopy (cryo-EM) maps is challenging and error prone. We have developed MEDIC (Model Error Detection in Cryo-EM), a robust statistical model that identifies local backbone errors in protein structures built into cryo-EM maps by combining local fit-to-density with deep-learning-derived structural information. MEDIC is validated on a set of 28 structures that were subsequently solved to higher resolutions, where we identify the differences between low- and high-resolution structures with 68
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:37253357
%U <Go to ISI:>//WOS:001042128600001
%R 10.1016/j.str.2023.05.002
%U https://bib-pubdb1.desy.de/record/600207