Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo‐Electron Microscopy Maps
Please always quote using this URN: urn:nbn:de:bvb:20-opus-214763
- In recent years, three‐dimensional density maps reconstructed from single particle images obtained by electron cryo‐microscopy (cryo‐EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the constituting structures require de‐novo model building or are very mobile. Herein, we demonstrate the potential of convolutional neural networks for the annotation of cryo‐EM maps: our network Haruspex has been trained on a carefully curated set of 293 experimentally derived reconstruction maps toIn recent years, three‐dimensional density maps reconstructed from single particle images obtained by electron cryo‐microscopy (cryo‐EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the constituting structures require de‐novo model building or are very mobile. Herein, we demonstrate the potential of convolutional neural networks for the annotation of cryo‐EM maps: our network Haruspex has been trained on a carefully curated set of 293 experimentally derived reconstruction maps to automatically annotate RNA/DNA as well as protein secondary structure elements. It can be straightforwardly applied to newly reconstructed maps in order to support domain placement or as a starting point for main‐chain placement. Due to its high recall and precision rates of 95.1 % and 80.3 %, respectively, on an independent test set of 122 maps, it can also be used for validation during model building. The trained network will be available as part of the CCP‐EM suite.…
Author: | Philipp Mostosi, Hermann Schindelin, Philip Kollmannsberger, Andrea Thorn |
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URN: | urn:nbn:de:bvb:20-opus-214763 |
Document Type: | Journal article |
Faculties: | Fakultät für Biologie / Rudolf-Virchow-Zentrum |
Language: | English |
Parent Title (English): | Angewandte Chemie International Edition |
Year of Completion: | 2020 |
Volume: | 59 |
Issue: | 35 |
First Page: | 14788 |
Last Page: | 14795 |
Source: | Angewandte Chemie International Edition 59(35):14788-14795. DOI: 10.1002/anie.202000421 |
DOI: | https://doi.org/10.1002/anie.202000421 |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
Tag: | DNA structures; RNA structures; electron microscopy; neural networks; protein structures |
Release Date: | 2021/04/20 |
Licence (German): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |