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Bioinformatics Advance Access published online on May 6, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth291
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received November 19, 2003
Revised April 6, 2004
Accepted April 23, 2004

Article

Distribution of information in biomedical abstracts and full-text publications

M. J. Schuemie 1*, M. Weeber 1, B. J. A. Schijvenaars 1, E. M. van Mulligen 1, C. C. van der Eijk 1, R. Jelier 1, B. Mons 1, J. A. Kors 1

1 Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, the Netherlands

* To whom correspondence should be addressed. E-mail: m.schuemie{at}erasmusmc.nl.


  Abstract

Motivation: Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full-text over abstracts in terms of information content and occurrences of gene symbol - gene name combinations that can resolve gene-symbol ambiguity.

Results: We analyzed a set of 3,902 biomedical full-text articles. Different keyword measures indicate that information density is highest in abstracts, but that the information coverage in full-texts is much greater than in abstracts. Analysis of five different standard sections of articles shows that the highest information coverage is located in the results section. Still, 30% to 40% of the information mentioned in each section is unique to that section.

Only 30% of the gene symbols in the abstract are accompanied by their corresponding names, and a further 8% of the gene names are found in the full-text. In the full-text, only 18% of the gene symbols are accompanied by their gene names.


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