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Nucleic Acids Research 2005 33(Web Server Issue):W774-W778; doi:10.1093/nar/gki429
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© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oupjournals.org

Article

PubFinder: a tool for improving retrieval rate of relevant PubMed abstracts

Thomas Goetz and Claus-Wilhelm von der Lieth*

Central Spectroscopy Department (B090)–Molecular, Modeling, German Cancer Research Center Heidelberg Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany

*To whom correspondence should be addressed. Tel: +49 6221 424541; Email: vonderlieth{at}dkfz-heidelberg.de

Received February 14, 2005. Revised March 24, 2005. Accepted March 24, 2005.

Since it is becoming increasingly laborious to manually extract useful information embedded in the ever-growing volumes of literature, automated intelligent text analysis tools are becoming more and more essential to assist in this task. PubFinder (www.glycosciences.de/tools/PubFinder) is a publicly available web tool designed to improve the retrieval rate of scientific abstracts relevant for a specific scientific topic. Only the selection of a representative set of abstracts is required, which are central for a scientific topic. No special knowledge concerning the query-syntax is necessary. Based on the selected abstracts, a list of discriminating words is automatically calculated, which is subsequently used for scoring all defined PubMed abstracts for their probability of belonging to the defined scientific topic. This results in a hit-list of references in the descending order of their likelihood score. The algorithms and procedures implemented in PubFinder facilitate the perpetual task for every scientist of staying up-to-date with current publications dealing with a specific subject in biomedicine.


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