Skip Navigation


Bioinformatics Advance Access first published online on November 15, 2007
This version published online on November 21, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm557
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrowOA All Versions of this Article:
24/2/296    most recent
btm557v2
btm557v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Rebholz-Schuhmann, D.
Right arrow Articles by Jimeno, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Rebholz-Schuhmann, D.
Right arrow Articles by Jimeno, A.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Text processing through Web services: Calling Whatizit

Dietrich Rebholz-Schuhmann 1,*, Miguel Arregui 1, Sylvain Gaudan 1, Harald Kirsch and Antonio Jimeno 1

1European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, U.K

*To whom correspondence should be addressed. Dr. Dietrich Rebholz-Schuhmann, E-mail: rebholz{at}ebi.ac.uk


  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 inhouse 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)

Associate Editor: Dr. Jonathan Wren

Received on July 10, 2007; revised on October 2, 2007; accepted on November 4, 2007

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.