{"doi":"10.1016/j.csbj.2024.06.018","title":"CORACLE ( <u>CO</u> VID-19 lite <u>RA</u> ture <u>C</u> ompi <u>LE</u> r): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement","abstract":"Background: During the COVID-19 pandemic a need to process large volumes of publications emerged. As the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID-19 (PASC) - that affects over 10 % of those who contract SARS-CoV-2 and presents a significant challenge in the medical field. The continuous influx of publications underscores a need for efficient tools for navigating the literature. Objectives: We aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to identify key publications and networks. Methods: We introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed to analyse COVID-19-related scientific articles and to identify research trends. CORACLE features three primary interfaces: The \"Search\" interface, which displays research trends and citation links; the \"Citation Map\" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the \"MeSH\" interface, highlighting current MeSH trends and their associations. Results: CORACLE leverages PubMed data to categorize literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. Conclusion: CORACLE is an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of emerging trends in COVID-19 and PASC research.","journal":"Computational and Structural Biotechnology Journal","year":2024,"id":480470,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9157,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1320366,"name":"Yulian Luo","orcid":null,"position":1,"is_corresponding":false},{"id":1320052,"name":"Pia Lindberg","orcid":"0000-0002-5679-4714","position":2,"is_corresponding":false},{"id":1320053,"name":"Jing Gao","orcid":"0000-0002-7732-456X","position":3,"is_corresponding":false},{"id":1320054,"name":"Michael Runold","orcid":"0000-0001-7568-2278","position":4,"is_corresponding":false},{"id":1320055,"name":"Iryna Kolosenko","orcid":"0000-0003-3988-1784","position":5,"is_corresponding":false},{"id":467155,"name":"Chuanxing Li","orcid":"0000-0003-2189-5010","position":6,"is_corresponding":false},{"id":467157,"name":"Åsa M. Wheelock","orcid":"0000-0002-8013-2745","position":7,"is_corresponding":false},{"id":1320365,"name":"Kristina Piontkovskaya","orcid":null,"position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-19T02:07:02.142014Z","pmid":"39027652","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":[]}