Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloThe BioLexicon: a large-scale terminological resource for biomedical text mining
Anno di pubblicazione2011
FormatoElettronico
Autore/iPaul Thompson, John McNaught, Simonetta Montemagni, Nicoletta Calzolari, Riccardo del Gratta, Vivian Lee, Simone Marchi, Monica Monachini, Piotr Pezik, Valeria Quochi, CJ Rupp, Yutaka Sasaki, Giulia Venturi, Dietrich Rebholz-Schuhmann, Sophia Ananiadou
Affiliazioni autoriSchool of Computer Science, University of Manchester; National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester; Manchester Interdisciplinary Biocentre, University of Manchester; Istituto di Linguistica Computazionale del CNR; European Bioinformatics Institute, Wellcome Trust Genome Campus; Toyota Technological Institute
Autori CNR e affiliazioni
  • GIULIA VENTURI
  • SIMONETTA MONTEMAGNI
  • MONICA MONACHINI
  • SIMONE MARCHI
  • VALERIA QUOCHI
  • RICCARDO DEL GRATTA
  • NICOLETTA ZAMORANI
Lingua/e
  • inglese
AbstractBackground Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. Results This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard. Conclusions The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da1
Pagine a29
Pagine totali29
RivistaBMC bioinformatics
Attiva dal 2000
Editore: BioMed Central, - [London]
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 1471-2105
Titolo chiave: BMC bioinformatics
Titolo proprio: BMC bioinformatics
Titolo abbreviato: BMC bioinformatics
Titoli alternativi:
  • BioMed Central bioinformatics
  • Bioinformatics
Numero volume della rivista12
Fascicolo della rivista397
DOI10.1186/1471-2105-12-397
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-80053915290)
  • ISI Web of Science (WOS) (Codice:000297641800001)
Parole chiaveText Mining, Information Extraction, Computational Lexicon
Link (URL, URI)http://www.biomedcentral.com/1471-2105/12/397
Titolo parallelo-
Data di accettazione-
Note/Altre informazioniID_PUMA: cnr.ilc/2011-A0-011
Strutture CNR
  • ILC — Istituto di linguistica computazionale "Antonio Zampolli"
Moduli/Attività/Sottoprogetti CNR
  • IC.P02.004.001 : Tecnologie linguistiche e gestione della conoscenza
  • IC.P02.005.001 : Risorse e Tecnologie Linguistiche: modelli, metodi di sviluppo, applicazioni, disegno di strategie internazionali
Progetti Europei-
Allegati