Will talk about: Integrating and ranking the evidence from pathways to text
Sophia Ananiadou is Professor of Computer Science in the School of Computer Science, the University of Manchester and director of the National Centre for Text Mining (NaCTeM).She has established a strong track record over the past decade, building NaCTeM with +15 staff, substantial infrastructure in text mining and active collaborations with industry and academia internationally. Her research includes the development of large-scale resources for biology (BioLexicon), data integration using text mining, event extraction for drug discovery, pathway reconstruction and association mining, text mining tools for education, chemistry, social sciences, institutional repositories and systematic reviews. She is developing text mining services for EuropePubMedCentral, funded by Wellcome Trust. She has authored over 230 publications, is regular speaker at conferences (keynote at e.g. IHI 2012, IC3K 2012, CICLing 2013).
PathText is a text mining system associating pathway models encoded in SBML with evidence from the literature. The strengths of PathText include integration with text mining semantic search services, Facta+, KLEIO, MEDIE, query generation and document-reaction relevance ranking. These services include event extraction tools (EventMine), faceted search based on named entity recognition, disambiguation components and normalisation. In addition, a one-stop collaborative text processing workflow platform (Argo) includes annotation tools that facilitate curation of pathways.