Detecting and analysing contrasts and contradictions are promising aspects in science, as they suggest further research potentials and discoveries. Finding contrasts and contradictions in text by means of automatic methods is a relatively new area in text mining. Specifically, most biological text mining research has so far focused on mining affirmative statements about the relations amongst entities, although it is of growing interest to find reports on weak or negative relations, or lack thereof. Negation detection is a middle step to finding contrasts and contradictions, and has been of special interest in medical text mining, due to the abundance of negative patterns in medical descriptions.
The aim of this research is to develop text mining methods to detect and analyse contrasting facts in the biomedical literature
and, specifically, the protein-protein interactions between the HIV-1 virus and the human host.
- 2012, Martin Gerner*, Farzaneh Sarafraz*, Casey M Bergman, Goran Nenadic. "BioContext: an integrated text mining system for large-scale extraction and contextualisation of biomolecular events" Journal of Bioinformatics, Oxford University Press.
- 2012, Daniel G Jamieson, Martin Gerner, Farzaneh Sarafraz, Goran Nenadic, and David L Robertson. "2012, Towards semi-automated curation: using text mining to recreate the HIV-1, human protein interaction database" Database: The Journal of Biological Databases and Curation, Oxford University Press.
- 2010, Farzaneh Sarafraz and Goran Nenadić. "Identification of Negated Regulation Events in the Literature: Exploring the Feature Space" Fourth International Symposium on Semantic Mining in Biomedicine (SMBM). (paper, poster.)
- 2010, Irena Spasić, Farzaneh Sarafraz, John A. Keane, Goran Nenadić. "Medication information extraction with linguistic pattern matching and semantic rules" Journal of the American Medical Informatics Association, Vol. 17, No. 5, pp. 532-535. (PMID: 20819858, DOI: 10.1136/jamia.2010.003657.)
- 2010, Farzaneh Sarafraz and Goran Nenadic. "Using SVMs with the Command Relation Features to Identify Negated Events in Biomedical Literature." The Workshop on Negation and Speculation in Natural Language Processing. (paper.)
- 2009, Irena Spasic, Farzaneh Sarafraz, John Keane, and Goran Nenadic. "Medication Information Extraction with Linguistic Pattern Matching and Semantic Rules" Proceedings of the i2b2 2009 Workshop.
- 2009, Farzaneh Sarafraz, James Eales, Reza Mohammadi, Jonathan Dickerson, David Robertson and Goran Nenadic. "Biomedical Event Detection using Rules, Conditional Random Fields and Parse Tree Distances." Paper presented at the Proceedings of the BioNLP 2009 Workshop Companion Volume for the Shared Task in Event Extraction. (paper, poster.)