- The amount of scientific literature published is growing exponentially and researchers are finding it increasingly difficult to keep up with new findings. Literature-based discovery (LBD) systems attempt to address this situation by using data-driven approaches to uncover new, potentially meaningful relations between entities that could lead to new discoveries. LBD systems combine concepts from disparate sources potentially leading to new inferences in scientific understanding.
- Scientific-LBD -- A freely available python package for literature-based discovery using set association measures.
- ALBD -- A freely available perl suit for literature-based discovery using set association measures.
literature based discovery to gain insights into the metabolomic processes
of cardiac arrest.
Sam Henry, Dayanjan S. Wijesinghe, Aidan Meyers, and Bridget McInnes.
Frontiers in Research Metrics and Analytics. 6 (2021): 32.
- Indirect association and ranking hypotheses for literature based discovery.
Sam Henry and Bridget T. McInnes.
BMC bioinformatics 20 (1), 425, 2019.
- A Literature Based Discovery Visualization System with Hierarchical Clustering and Linking Set Associations.
Sam Henry, Ali Panahi, Dayanjan S. Wijesinghe and Bridget T. McInnes.
In Proceedings of the AMIA Summits on Translational Science, pp. 582, 2019.
- Semantic association for literature based discovery.
Sam Henry and Bridget McInnes.
In Proceedings of the American Medical Informatics Association. November 2017. (poster)
- Linking Term Association: ranking implicit terms in literature-based discovery.
In Proceedings of the American Medical Informatics Association Graduate Student NLP-WG Workshop. November 2017. (poster)
- Literature Based Discovery: models, methods and trends.
Sam Henry and Bridget McInnes. Journal of Biomedical Informatics (JBI), Volume 74, pages 20-32, October 2017.