Literature DB >> 18006544

Text processing through Web services: calling Whatizit.

Dietrich Rebholz-Schuhmann1, Miguel Arregui, Sylvain Gaudan, Harald Kirsch, Antonio Jimeno.   

Abstract

MOTIVATION: Text-mining (TM) solutions are developing into efficient services to researchers in the biomedical research community. Such solutions have to scale with the growing number and size of resources (e.g. available controlled vocabularies), with the amount of literature to be processed (e.g. about 17 million documents in PubMed) and with the demands of the user community (e.g. different methods for fact extraction). These demands motivated the development of a server-based solution for literature analysis. Whatizit is a suite of modules that analyse text for contained information, e.g. any scientific publication or Medline abstracts. Special modules identify terms and then link them to the corresponding entries in bioinformatics databases such as UniProtKb/Swiss-Prot data entries and gene ontology concepts. Other modules identify a set of selected annotation types like the set produced by the EBIMed analysis pipeline for proteins. In the case of Medline abstracts, Whatizit offers access to EBI's in-house installation via PMID or term query. For large quantities of the user's own text, the server can be operated in a streaming mode (http://www.ebi.ac.uk/webservices/whatizit).

Entities:  

Mesh:

Year:  2007        PMID: 18006544     DOI: 10.1093/bioinformatics/btm557

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  82 in total

1.  Beyond accuracy: creating interoperable and scalable text-mining web services.

Authors:  Chih-Hsuan Wei; Robert Leaman; Zhiyong Lu
Journal:  Bioinformatics       Date:  2016-02-16       Impact factor: 6.937

2.  Ontology based text mining of gene-phenotype associations: application to candidate gene prediction.

Authors:  Şenay Kafkas; Robert Hoehndorf
Journal:  Database (Oxford)       Date:  2019-01-01       Impact factor: 3.451

3.  Biomedical ontologies in action: role in knowledge management, data integration and decision support.

Authors:  O Bodenreider
Journal:  Yearb Med Inform       Date:  2008

4.  OnTheFly: a tool for automated document-based text annotation, data linking and network generation.

Authors:  Georgios A Pavlopoulos; Evangelos Pafilis; M Kuhn; Sean D Hooper; Reinhard Schneider
Journal:  Bioinformatics       Date:  2009-02-17       Impact factor: 6.937

5.  Biomedical text mining and its applications.

Authors:  Raul Rodriguez-Esteban
Journal:  PLoS Comput Biol       Date:  2009-12-24       Impact factor: 4.475

6.  Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD).

Authors:  Thomas C Wiegers; Allan Peter Davis; K Bretonnel Cohen; Lynette Hirschman; Carolyn J Mattingly
Journal:  BMC Bioinformatics       Date:  2009-10-08       Impact factor: 3.169

7.  Annotation of protein residues based on a literature analysis: cross-validation against UniProtKb.

Authors:  Kevin Nagel; Antonio Jimeno-Yepes; Dietrich Rebholz-Schuhmann
Journal:  BMC Bioinformatics       Date:  2009-08-27       Impact factor: 3.169

8.  A realistic assessment of methods for extracting gene/protein interactions from free text.

Authors:  Renata Kabiljo; Andrew B Clegg; Adrian J Shepherd
Journal:  BMC Bioinformatics       Date:  2009-07-28       Impact factor: 3.169

9.  From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways.

Authors:  Anna Bauer-Mehren; Laura I Furlong; Michael Rautschka; Ferran Sanz
Journal:  BMC Bioinformatics       Date:  2009-08-27       Impact factor: 3.169

10.  Comparison of concept recognizers for building the Open Biomedical Annotator.

Authors:  Nigam H Shah; Nipun Bhatia; Clement Jonquet; Daniel Rubin; Annie P Chiang; Mark A Musen
Journal:  BMC Bioinformatics       Date:  2009-09-17       Impact factor: 3.169

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