RetroMine, or how to provide in-depth retrospective studies from Medline in a glance: the hepcidin use-case

Bertrand Ameline de Cadeville 1 , Olivier Loréal 2 ,  and Fouzia Moussouni-Marzolf 1 , 3
  • 1 Université de Rennes 1, Faculté de Médecine, 35043, Rennes, France
  • 2 INSERM UMR 991, CHU Pontchaillou, 35033, Rennes, France
  • 3 INSERM UMR 991, CHU Pontchaillou, 35033, Rennes, France


The rapid expansion of biomedical literature has provoked an increased development of advanced text mining tools to rapidly extract relevant events from the continuously increasing amount of knowledge published periodically in PubMed. However, bioinvestigators are still reluctant to use these tools for two reasons: i) a large volume of events is often extracted upon a query, and this volume is hard to manage, and ii) background events dominate search results and overshadow more pertinent published information, especially for domain experts. In this paper, we propose an approach that incorporates the temporal dimension of published events to the process of information extraction to improve data selection and prioritize more pertinent periodically published knowledge for scientists. Indeed, instead of providing the total knowledge associated with a PubMed query, which is usually a mix of trivial background information and nonbackground information, we propose a method that incorporates time and selects non background and highly relevant biological entities and events published over time for bioinvestigators. Before excluding background events from the total knowledge extracted, a quantification of their amount is also provided. This work is illustrated by a case study regarding Hepcidin gene publications over a decade, a duration that is sufficiently long enough to generate alternative views on the overall data extracted.

If the inline PDF is not rendering correctly, you can download the PDF file here.


Journal + Issues

The Journal of Integrative Bioinformatics is an international journal dedicated to methods and tools of computer science and electronic infrastructure applied to biotechnology. The journal covers mainly but not exclusively data/method integration, modeling, simulation and visualization in combination with applications of theoretical/computational tools and any other approach supporting an integrative view of complex biological systems.