Evidence map›Paper›PMID 41310054›Full record

ArticleNature methods2026

A comprehensive foundation model for cryo-EM image processing.

Yang Yan, Shiqi Fan, Fajie Yuan, Huaizong Shen

Abstract read
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In one paragraph

Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yang Yan *Research Center for Industries of the Future, Westlake University, Hangzhou, China.ORCID http://orcid.org/0000-0002-3306-3863
Shiqi Fan *Research Center for Industries of the Future, Westlake University, Hangzhou, China.ORCID http://orcid.org/0009-0009-9278-8889
Fajie YuanResearch Center for Industries of the Future, Westlake University, Hangzhou, China. yuanfajie@westlake.edu.cn.ORCID http://orcid.org/0000-0001-8452-9929
Huaizong ShenResearch Center for Industries of the Future, Westlake University, Hangzhou, China. shenhuaizong@westlake.edu.cn.ORCID http://orcid.org/0000-0002-1216-5393

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2022ZD0115100Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2024YFA0916903National Natural Science Foundation of China (National Science Foundation of China) 32071208National Natural Science Foundation of China (National Science Foundation of China) 32122042National Natural Science Foundation of China (National Science Foundation of China) U21A20427Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) DQ24C050001
6 · The paper itself

Abstract

Cryogenic electron microscopy (cryo-EM) has become a premier technique for determining high-resolution structures of biological macromolecules. However, its broad application is constrained by the demand for specialized expertise. Here, to address this limitation, we introduce the Cryo-EM Image Evaluation Foundation (Cryo-IEF) model, a versatile tool pre-trained on ~65 million cryo-EM particle images through unsupervised learning. Cryo-IEF performs diverse cryo-EM processing tasks, including particle classification by structure, pose-based clustering and image quality assessment. Building on this foundation, we developed CryoWizard, a fully automated single-particle cryo-EM processing pipeline enabled by fine-tuned Cryo-IEF for efficient particle quality ranking. CryoWizard resolves high-resolution structures across samples of varied properties and effectively mitigates the prevalent challenge of preferred orientation in cryo-EM.

Indexed as

Cryoelectron MicroscopyImage Processing, Computer-AssistedAlgorithmsMacromolecular SubstancesSoftwareMacromolecular Substances

Identifiers

What OpenQuestion holds

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Registered trials

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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.