{"doi":"10.1101/2020.11.05.368969","title":"NERO: A Biomedical Named-entity (Recognition) Ontology with a Large, Annotated Corpus Reveals Meaningful Associations Through Text Embedding","abstract":"Machine reading is essential for unlocking valuable knowledge contained in the millions of existing biomedical documents. Over the last two decades 1,2 , the most dramatic advances in machine-reading have followed in the wake of critical corpus development 3 . Large, well-annotated corpora have been associated with punctuated advances in machine reading methodology and automated knowledge extraction systems in the same way that ImageNet 4 was fundamental for developing machine vision techniques. This study contributes six components to an advanced, named-entity analysis tool for biomedicine: (a) a new, Named-Entity Recognition Ontology (NERO) developed specifically for describing entities in biomedical texts, which accounts for diverse levels of ambiguity, bridging the scientific sublanguages of molecular biology, genetics, biochemistry, and medicine; (b) detailed guidelines for human experts annotating hundreds of named-entity classes; (c) pictographs for all named entities, to simplify the burden of annotation for curators; (d) an original, annotated corpus comprising 35,865 sentences, which encapsulate 190,679 named entities and 43,438 events connecting two or more entities; (e) validated, off-the-shelf, named-entity recognition automated extraction, and; (f) embedding models that demonstrate the promise of biomedical associations embedded within this corpus.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":125523,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8638,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":49287,"name":"Robert Stevens","orcid":"0000-0002-6038-9025","position":1,"is_corresponding":false},{"id":571661,"name":"Halima Alachram","orcid":"0000-0002-4567-0775","position":2,"is_corresponding":false},{"id":571662,"name":"Yu Li","orcid":"0000-0002-3664-6722","position":3,"is_corresponding":false},{"id":14525,"name":"Larisa Soldatova","orcid":"0000-0001-6489-3029","position":4,"is_corresponding":false},{"id":571663,"name":"Ross D. King","orcid":"0000-0001-7208-4387","position":5,"is_corresponding":false},{"id":28813,"name":"Sophia Ananiadou","orcid":"0000-0002-4097-9191","position":6,"is_corresponding":false},{"id":571664,"name":"Maolin Li","orcid":"0000-0002-0828-2001","position":7,"is_corresponding":false},{"id":571665,"name":"Fenia Christopoulou","orcid":"0000-0001-5217-9848","position":8,"is_corresponding":false},{"id":54507,"name":"José Luis Ambite","orcid":"0000-0003-0087-080X","position":9,"is_corresponding":false},{"id":571666,"name":"Sahil Garg","orcid":"0000-0003-0229-608X","position":10,"is_corresponding":false},{"id":572116,"name":"Ulf Hermjakob","orcid":null,"position":11,"is_corresponding":false},{"id":572117,"name":"Daniel Marcu","orcid":"0000-0002-2151-5850","position":12,"is_corresponding":false},{"id":572118,"name":"Emily Sheng","orcid":null,"position":13,"is_corresponding":false},{"id":571667,"name":"Tim Beißbarth","orcid":"0000-0001-6509-2143","position":14,"is_corresponding":false},{"id":571668,"name":"Edgar Wingender","orcid":"0000-0002-7729-8453","position":15,"is_corresponding":false},{"id":257766,"name":"Aram Galstyan","orcid":"0000-0003-4215-0886","position":16,"is_corresponding":false},{"id":383211,"name":"Xin Gao","orcid":"0000-0002-7108-3574","position":17,"is_corresponding":false},{"id":571669,"name":"Chambers Brendan","orcid":"0000-0001-9138-6452","position":18,"is_corresponding":false},{"id":571670,"name":"Bohdan B. Khomtchouk","orcid":"0000-0001-9607-7528","position":19,"is_corresponding":false},{"id":44579,"name":"James A. Evans","orcid":"0000-0001-9838-0707","position":20,"is_corresponding":false},{"id":229003,"name":"Andrey Rzhetsky","orcid":"0000-0001-6959-7405","position":21,"is_corresponding":false},{"id":571660,"name":"Kanix Wang","orcid":"0000-0003-1355-577X","position":0,"is_corresponding":true}],"reference_count":30,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:15:15.482227Z","pmid":null,"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":[]}