{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T13:04:29Z","timestamp":1769605469916,"version":"3.49.0"},"reference-count":55,"publisher":"Oxford University Press (OUP)","issue":"13","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":1937,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.5"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Discovering useful associations between biomedical concepts has been one of the main goals in biomedical text-mining, and understanding their biomedical contexts is crucial in the discovery process. Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner.<\/jats:p><jats:p>Results: This article describes FACTA+, a real-time text-mining system for finding and visualizing indirect associations between biomedical concepts from MEDLINE abstracts. The system can be used as a text search engine like PubMed with additional features to help users discover and visualize indirect associations between important biomedical concepts such as genes, diseases and chemical compounds. FACTA+ inherits all functionality from its predecessor, FACTA, and extends it by incorporating three new features: (i) detecting biomolecular events in text using a machine learning model, (ii) discovering hidden associations using co-occurrence statistics between concepts, and (iii) visualizing associations to improve the interpretability of the output. To the best of our knowledge, FACTA+ is the first real-time web application that offers the functionality of finding concepts involving biomolecular events and visualizing indirect associations of concepts with both their categories and importance.<\/jats:p><jats:p>Availability: FACTA+ is available as a web application at http:\/\/refine1-nactem.mc.man.ac.uk\/facta\/, and its visualizer is available at http:\/\/refine1-nactem.mc.man.ac.uk\/facta-visualizer\/.<\/jats:p><jats:p>Contact: \u00a0tsuruoka@jaist.ac.jp<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr214","type":"journal-article","created":{"date-parts":[[2011,6,17]],"date-time":"2011-06-17T23:32:32Z","timestamp":1308353552000},"page":"i111-i119","source":"Crossref","is-referenced-by-count":97,"title":["Discovering and visualizing indirect associations between biomedical concepts"],"prefix":"10.1093","volume":"27","author":[{"given":"Yoshimasa","family":"Tsuruoka","sequence":"first","affiliation":[{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"}]},{"given":"Makoto","family":"Miwa","sequence":"additional","affiliation":[{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"},{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"},{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"}]},{"given":"Kaisei","family":"Hamamoto","sequence":"additional","affiliation":[{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"}]},{"given":"Jun'ichi","family":"Tsujii","sequence":"additional","affiliation":[{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"},{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"},{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"}]},{"given":"Sophia","family":"Ananiadou","sequence":"additional","affiliation":[{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"},{"name":"1 School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, 2Department of Computer Science, The University of Tokyo, Tokyo, Japan, 3The National Centre for Text Mining (NaCTeM), 4School of Computer Science, The University of Manchester, Manchester, UK and 5Microsoft Research Asia, Beijing, China"}]}],"member":"286","published-online":{"date-parts":[[2011,6,14]]},"reference":[{"issue":"Suppl. 11","key":"2023012512015793000_B1","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1471-2105-9-S11-S2","article-title":"All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning","volume":"9","author":"Airola","year":"2008","journal-title":"BMC bioinformatics"},{"key":"2023012512015793000_B2","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.tibtech.2010.04.005","article-title":"Event extraction for systems biology by text mining the literature","volume":"28","author":"Ananiadou","year":"2010","journal-title":"Trends in Biotechnol."},{"key":"2023012512015793000_B3","first-page":"10","article-title":"Extracting complex biological events with rich graph-based feature sets","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Bj\u00f6rne","year":"2009"},{"key":"2023012512015793000_B4","doi-asserted-by":"crossref","first-page":"i382","DOI":"10.1093\/bioinformatics\/btq180","article-title":"Complex event extraction at PubMed scale","volume":"26","author":"Bjorne","year":"2010","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B5","first-page":"14","article-title":"The frame-based module of the suiseki information extraction system","volume":"17","author":"Blaschke","year":"2002","journal-title":"IEEE Intell. Syst."},{"key":"2023012512015793000_B6","first-page":"19","article-title":"Event extraction from trimmed dependency graphs","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Buyko","year":"2009"},{"key":"2023012512015793000_B7","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1186\/1471-2105-5-147","article-title":"Content-rich biological network constructed by mining pubmed abstracts","volume":"5","author":"Chen","year":"2004","journal-title":"BMC Bioinformatics"},{"key":"2023012512015793000_B8","first-page":"50","article-title":"High-precision biological event extraction with a concept recognizer","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Cohen","year":"2009"},{"issue":"Suppl. 10","key":"2023012512015793000_B9","doi-asserted-by":"crossref","first-page":"S7","DOI":"10.1186\/1471-2105-10-S10-S7","article-title":"Goweb: a semantic search engine for the life science web","volume":"10","author":"Dietze","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2023012512015793000_B10","doi-asserted-by":"crossref","first-page":"2138","DOI":"10.1093\/bioinformatics\/bti296","article-title":"BioIE: extracting informative sentences from the biomedical literature","volume":"21","author":"Divoli","year":"2005","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B11","doi-asserted-by":"crossref","first-page":"W406","DOI":"10.1093\/nar\/gkn215","article-title":"CoPub: a literature-based keyword enrichment tool for microarray data analysis","volume":"36","author":"Frijters","year":"2008","journal-title":"Nucleic Acids Res."},{"key":"2023012512015793000_B12","doi-asserted-by":"crossref","first-page":"e1000943","DOI":"10.1371\/journal.pcbi.1000943","article-title":"Literature mining for the discovery of hidden connections between drugs, genes and diseases","volume":"6","author":"Frijters","year":"2010","journal-title":"PLoS Comput. Biol."},{"key":"2023012512015793000_B13","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.2217\/pgs.10.136","article-title":"Recent progress in automatically extracting information from the pharmacogenomic literature","volume":"11","author":"Garten","year":"2010","journal-title":"Pharmacogenomics"},{"key":"2023012512015793000_B14","first-page":"86","article-title":"Molecular event extraction from link grammar parse trees","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Hakenberg","year":"2009"},{"issue":"Suppl. 2","key":"2023012512015793000_B15","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1093\/bioinformatics\/bti1142","article-title":"Implementing the iHOP concept for navigation of biomedical literature","volume":"21","author":"Hoffmann","year":"2005","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B16","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.ijmedinf.2004.04.024","article-title":"Using literature-based discovery to identify disease candidate genes","volume":"74","author":"Hristovski","year":"2005","journal-title":"Inter. J. Med. Infor."},{"key":"2023012512015793000_B17","doi-asserted-by":"crossref","first-page":"3604","DOI":"10.1093\/bioinformatics\/bth451","article-title":"Discovering patterns to extract protein-protein interactions from full texts","volume":"20","author":"Huang","year":"2004","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B18","doi-asserted-by":"crossref","first-page":"R96","DOI":"10.1186\/gb-2008-9-6-r96","article-title":"Anni 2.0: a multipurpose text-mining tool for the life sciences","volume":"9","author":"Jelier","year":"2008","journal-title":"Genome Biol."},{"key":"2023012512015793000_B19","first-page":"28","article-title":"Uzurich in the bionlp 2009 shared task","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Kaljurand","year":"2009"},{"key":"2023012512015793000_B20","doi-asserted-by":"crossref","first-page":"i374","DOI":"10.1093\/bioinformatics\/btq221","article-title":"PathText: a text mining integrator for biological pathway visualizations","volume":"26","author":"Kemper","year":"2010","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B21","first-page":"119","article-title":"Syntactic dependency based heuristics for biological event extraction","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Kilicoglu","year":"2009"},{"key":"2023012512015793000_B22","first-page":"69","article-title":"Semantic MEDLINE: a web application to manage the results of PubMed searches","volume-title":"Proceedings of the Third International Symposium on Semantic Mining in Biomedicine (SMBM 2008)","author":"Kilicoglu","year":"2008"},{"key":"2023012512015793000_B23","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/1471-2105-9-10","article-title":"Corpus annotation for mining biomedical events from literature","volume":"9","author":"Kim","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2023012512015793000_B24","first-page":"1","article-title":"Overview of bionlp'09 shared task on event extraction","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Kim","year":"2009"},{"key":"2023012512015793000_B25","first-page":"46","article-title":"Importance of negations and experimental qualifiers in biomedical literature","volume-title":"Proceedings of the Workshop on Negation and Speculation in Natural Language Processing","author":"Krallinger","year":"2010"},{"key":"2023012512015793000_B26","first-page":"282","article-title":"Conditional random fields: Probabilistic models for segmenting and labeling sequence data","volume-title":"Proceedings of the 18th International Conference on Machine Learning (ICML)","author":"Lafferty","year":"2001"},{"key":"2023012512015793000_B27","doi-asserted-by":"crossref","first-page":"e1000215","DOI":"10.1371\/journal.pcbi.1000215","article-title":"Biomedical discovery acceleration, with applications to craniofacial development","volume":"5","author":"Leach","year":"2009","journal-title":"PLoS Comput. Biol."},{"key":"2023012512015793000_B28","first-page":"77","article-title":"Biomedical event annotation with crfs and precision grammars","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"MacKinlay","year":"2009"},{"key":"2023012512015793000_B29","doi-asserted-by":"crossref","first-page":"e39","DOI":"10.1016\/j.ijmedinf.2009.04.010","article-title":"Protein-protein interaction extraction by leveraging multiple kernels and parsers","volume":"78","author":"Miwa","year":"2009","journal-title":"Inter. J. Med. Infor."},{"key":"2023012512015793000_B30","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1142\/S0219720010004586","article-title":"Event extraction with complex event classification using rich features","volume":"8","author":"Miwa","year":"2010","journal-title":"J. Bioinformatics Comput. Biol."},{"key":"2023012512015793000_B31","first-page":"1017","article-title":"Semantic retrieval for the accurate identification of relational concepts in massive textbases","volume-title":"Proceedings of the 21th international Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING\/ACL)","author":"Miyao","year":"2006"},{"key":"2023012512015793000_B32","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1093\/bioinformatics\/btn631","article-title":"Evaluating contributions of natural language parsers to protein-protein interaction extraction","volume":"25","author":"Miyao","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B33","first-page":"59","article-title":"A memory-based learning approach to event extraction in biomedical texts","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Morante","year":"2009"},{"key":"2023012512015793000_B34","first-page":"69","article-title":"Evaluating a meta-knowledge annotation scheme for bio-events","volume-title":"Proceedings of the Workshop on Negation and Speculation in Natural Language Processing","author":"Nawaz","year":"2010"},{"key":"2023012512015793000_B35","first-page":"68","article-title":"Extraction of biomedical events using case-based reasoning","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Neves","year":"2009"},{"key":"2023012512015793000_B36","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1145\/1390334.1390504","article-title":"Kleio: a knowledge-enriched information retrieval system for biology","volume-title":"Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"Nobata","year":"2008"},{"key":"2023012512015793000_B37","first-page":"465","article-title":"Improving the scalability of semi-markov conditional random fields for named entity recognition","volume-title":"Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING\/ACL)","author":"Okanohara","year":"2006"},{"key":"2023012512015793000_B38","first-page":"813","article-title":"Joint inference for knowledge extraction from biomedical literature","volume-title":"Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics","author":"Poon","year":"2010"},{"key":"2023012512015793000_B39","doi-asserted-by":"crossref","first-page":"e237","DOI":"10.1093\/bioinformatics\/btl302","article-title":"EBIMed\u2013text crunching to gather facts for proteins from MEDLINE","volume":"23","author":"Rebholz-Schuhmann","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B40","first-page":"41","article-title":"A markov logic approach to biomolecular event extraction","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Riedel","year":"2009"},{"key":"2023012512015793000_B41","first-page":"173","article-title":"Representing text chunks","volume-title":"Proceedings of the Ninth Conference of the European Chapter of the Association for Computational Linguistics (EACL)","author":"Sang","year":"1999"},{"key":"2023012512015793000_B42","first-page":"107","article-title":"Biomedical named entity recognition using conditional random fields and rich feature sets","volume-title":"COLING 2004 International Joint workshop on Natural Language Processing in Biomedicine and its Applications (NLPBA\/BioNLP) 2004","author":"Settles","year":"2004"},{"key":"2023012512015793000_B43","author":"Shneiderman","year":"2009","journal-title":"Treemaps for space-constrained visualization of hierarchies."},{"key":"2023012512015793000_B44","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.cmpb.2008.12.006","article-title":"Arrowsmith two-node search interface: a tutorial on finding meaningful links between two disparate sets of articles in MEDLINE","volume":"94","author":"Smalheiser","year":"2009","journal-title":"Comput. Methods Program. Biomed."},{"key":"2023012512015793000_B45","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1353\/pbm.1986.0087","article-title":"Fish oil, raynaud's syndrome, and undiscovered public knowledge","volume":"30","author":"Swanson","year":"1986","journal-title":"Pers. Biol. Med."},{"key":"2023012512015793000_B46","first-page":"29","article-title":"Medical literature as a potential source of new knowledge","volume":"78","author":"Swanson","year":"1990","journal-title":"Bull. Med. Libr. Assoc."},{"key":"2023012512015793000_B47","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/S0004-3702(97)00008-8","article-title":"An interactive system for finding complementary literatures: a stimulus to scientifc discovery","volume":"91","author":"Swanson","year":"1997","journal-title":"Artif. Intell."},{"key":"2023012512015793000_B48","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1093\/bioinformatics\/btn469","article-title":"FACTA: a text search engine for finding associated biomedical concepts","volume":"24","author":"Tsuruoka","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B49","first-page":"128","article-title":"Analyzing text in search of biomolecular events: a high-precision machine learning framework","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Van Landeghem","year":"2009"},{"key":"2023012512015793000_B50","first-page":"1","article-title":"Two strong baselines for the bionlp 2009 event extraction task","volume-title":"Proceedings of the 2010 Workshop on Biomedical Natural Language Processing","author":"Vlachos","year":"2010"},{"key":"2023012512015793000_B51","first-page":"37","article-title":"Biomedical event extraction without training data","volume-title":"Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task","author":"Vlachos","year":"2009"},{"key":"2023012512015793000_B52","first-page":"252","article-title":"Generating hypotheses by discovering implicit associations in the literature: a case report of a search for new potential therapeutic uses for thalidomide","volume":"10","author":"Weeber","year":"2003","journal-title":"JAMIA"},{"key":"2023012512015793000_B53","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1093\/bib\/6.3.277","article-title":"Online tools to support literature-based discovery in the life sciences","volume":"6","author":"Weeber","year":"2005","journal-title":"Brief. Bioinformatics"},{"key":"2023012512015793000_B54","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1093\/bioinformatics\/btg421","article-title":"Knowledge discovery by automated identification and ranking of implicit relationships","volume":"20","author":"Wren","year":"2004","journal-title":"Bioinformatics"},{"key":"2023012512015793000_B55","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1016\/j.jbi.2008.12.001","article-title":"A new evaluation methodology for literature-based discovery systems","volume":"42","author":"Yetisgen-Yildiz","year":"2009","journal-title":"J. Biomed. Inform."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/27\/13\/i111\/48880152\/bioinformatics_27_13_i111.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/27\/13\/i111\/48880152\/bioinformatics_27_13_i111.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,7]],"date-time":"2024-04-07T18:13:01Z","timestamp":1712513581000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/27\/13\/i111\/178661"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,6,14]]},"references-count":55,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2011,7,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btr214","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2011,7,1]]},"published":{"date-parts":[[2011,6,14]]}}}