ArticleNature communications2021
Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 46 citations in OpenAlex.
- Computational Approaches for Protein-DNA/RNA Complex Modeling for Cryo-EM Maps.Current protocols · 2026Article
- A Novel Machine-Learning Based Method for Resolving Secondary Structure Topology in Medium-Resolution Cryo-EM Density Maps.International journal of molecular sciences · 2026Article
- A comprehensive survey and benchmark of deep learning-based methods for atomic model building from cryo-electron microscopy density maps.Briefings in bioinformatics · 2025Article
- AI-based quality assessment methods for protein structure models from cryo-EM.Current research in structural biology · 2025Review
- Connecting the dots: deep learning-based automated model building methods in cryo-EM.Frontiers in molecular biosciences · 2025Review
- Protein Secondary Structure and DNA/RNA Detection for Cryo-EM and Cryo-ET Using Emap2sec and Emap2secMethods in molecular biology (Clifton, N.J.) · 2025Article
- Secondary Structure Detection and Structure Modeling for Cryo-EM.Methods in molecular biology (Clifton, N.J.) · 2025Article
- DiffModeler: large macromolecular structure modeling for cryo-EM maps using a diffusion model.Nature methods · 2024Article
- Unveiling the stochastic nature of human heteropolymer ferritin self-assembly mechanism.Protein science : a publication of the Protein Society · 2024Article
- DiffModeler: Large Macromolecular Structure Modeling in Low-Resolution Cryo-EM Maps Using Diffusion Model.bioRxiv : the preprint server for biology · 2024Article
- Bimodal DNA self-origami material with nucleic acid function enhancement.Journal of nanobiotechnology · 2024Article
- Assessment of Protein-Protein Docking Models Using Deep Learning.Methods in molecular biology (Clifton, N.J.) · 2024Review
- The combined focal loss and dice loss function improves the segmentation of beta-sheets in medium-resolution cryo-electron-microscopy density maps.Bioinformatics advances · 2024Article
- Integrated Protocol of Protein Structure Modeling for Cryo-EM with Deep Learning and Structure Prediction.bioRxiv : the preprint server for biology · 2023Article
- CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning.Nature methods · 2023Article
- An Approach to Developing Benchmark Datasets for Protein Secondary Structure Segmentation from Cryo-EM Density Maps.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy.Micromachines · 2023Review
- High-throughput cryo-ET structural pattern mining by unsupervised deep iterative subtomogram clustering.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A Machine Learning Method to Identify Umami Peptide Sequences by Using Multiplicative LSTM Embedded Features.Foods (Basel, Switzerland) · 2023Article
- Fast and automated protein-DNA/RNA macromolecular complex modeling from cryo-EM maps.Briefings in bioinformatics · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there are still substantial fractions of maps determined at intermediate or low resolutions, where extracting structure information is not trivial. Here, we report a new computational method, Emap2sec+, which identifies DNA or RNA as well as the secondary structures of proteins in cryo-EM maps of 5 to 10 Å resolution. Emap2sec+ employs the deep Residual convolutional neural network. Emap2sec+ assigns structural labels with associated probabilities at each voxel in a cryo-EM map, which will help structure modeling in an EM map. Emap2sec+ showed stable and high assignment accuracy for nucleotides in low resolution maps and improved performance for protein secondary structure assignments than its earlier version when tested on simulated and experimental maps.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.