Name
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 3902 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--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. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1093/bioinformatics/bth291 | Bioinformatics |
Keywords | Field | DocType |
tumor necrosis factor,interleukin 1 | Information coverage,Information density,Data mining,Information retrieval,Computer science,Bibliometrics,Bioinformatics,Ambiguity,MEDLINE,Gene nomenclature | Journal |
Volume | Issue | ISSN |
20 | 16 | 1367-4803 |
Citations | PageRank | References |
52 | 2.32 | 5 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martijn J. Schuemie | 1 | 529 | 34.40 |
| Marc Weeber | 2 | 457 | 34.63 |
| Bob J. A. Schijvenaars | 3 | 189 | 10.39 |
| Erik M. Van Mulligen | 4 | 633 | 44.63 |
| C. Christiaan Van Der Eijk | 5 | 155 | 10.47 |
| Rob Jelier | 6 | 209 | 11.21 |
| Barend Mons | 7 | 430 | 33.31 |
| Jan A. Kors | 8 | 635 | 37.25 |