{"doi":"10.1016/j.sbi.2025.102989","title":"AI-based methods for biomolecular structure modeling for Cryo-EM","abstract":"Cryo-electron microscopy (Cryo-EM) has revolutionized structural biology by enabling the determination of macromolecular structures that were challenging to study with conventional methods. Processing cryo-EM data involves several computational steps to derive three-dimensional structures from raw projections. Recent advancements in artificial intelligence (AI) including deep learning have significantly improved the performance of these processes. In this review, we discuss state-of-the-art AI-based techniques used in key steps of cryo-EM data processing, including macromolecular structure modeling and heterogeneity analysis. • Cryo-EM structure determination involves numerous computational data processing steps. • Many AI-based methods have been developed for cryo-EM data processing steps. • AI-based methods offer accurate, fast, or often unique capabilities for cryo-EM. • We discuss notable AI-based methods in seven key data processing steps in cryo-EM.","journal":"Current Opinion in Structural Biology","year":2025,"id":510940,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":17,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9516,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":558774,"name":"Genki Terashi","orcid":"0000-0002-5339-909X","position":1,"is_corresponding":false},{"id":1368127,"name":"Han Zhu","orcid":"0000-0001-6871-3777","position":2,"is_corresponding":false},{"id":316939,"name":"Daisuke Kihara","orcid":"0000-0003-4091-6614","position":3,"is_corresponding":false},{"id":1336387,"name":"Farhanaz Farheen","orcid":"0009-0006-5683-6853","position":0,"is_corresponding":true}],"reference_count":91,"raw_metadata":null,"created_at":"2026-07-19T02:47:50.575618Z","pmid":"39864242","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}