Improving links between literature and biological data with text mining: a case study with GEO, PDB and MEDLINE

Abstract

High-throughput experiments and bioinformatics techniques are creating an exploding volume of data that are becoming overwhelming to keep track of for biologists and researchers who need to access, analyze and process existing data. Much of the available data are being deposited in specialized databases, such as the Gene Expression Omnibus (GEO) for microarrays or the Protein Data Bank (PDB) for protein structures and coordinates. Data sets are also being described by their authors in publications archived in literature databases such as MEDLINE and PubMed Central. Currently, the curation of links between biological databases and the literature mainly relies on manual labour, which makes it a time-consuming and daunting task. Herein, we analysed the current state of link curation between GEO, PDB and MEDLINE. We found that the link curation is heterogeneous depending on the sources and databases involved, and that overlap between sources is low, <50% for PDB and GEO. Furthermore, we showed that text-mining tools can automatically provide valuable evidence to help curators broaden the scope of articles and database entries that they review. As a result, we made recommendations to improve the coverage of curated links, as well as the consistency of information available from different databases while maintaining high-quality curation. Database URLs: http://www.ncbi.nlm.nih.gov/PubMed, http://www.ncbi.nlm.nih.gov/geo/, http://www.rcsb.org/pdb/

Figure 1.

Excerpt from a sample GEO SOFT file.

Figure 2.

Excerpt from a sample MEDLINE citation.

Figure 3.

Overlap between GEO, MEDLINE (SI) and the results of text-mining on PMC; evidence statements were extracted from full-text articles for three categories that were outside the consensus between link sources: (I) Articles curated in MEDLINE but not by GEO, (II) articles curated by GEO but not by MEDLINE and (III) articles curated neither by MEDLINE nor GEO, but identified as relevant for link curation for GEO by our automatic tool.

Figure 4.

Overlap between PDB, MEDLINE (SI) and the results of text-mining on PMC; evidence statements were extracted from full-text articles for three categories that were outside the consensus between link sources: (I) Articles curated in MEDLINE but not by PDB, (II) articles curated by PDB but not by MEDLINE and (III) rticles curated neither by MEDLINE nor PDB, but identified as relevant for link curation for PDB by our automatic tool.