Date: 2013.12.16(Mon.) 15:00
Venue: Lecture Room Blue (B301), KI Bldg.
Host: Jong C. Park

Speaker:
Goran Nenadic, University of Manchester, UK

Title:
Contextualising biomedical text mining: from facts to contradictions

Abstract:
To date, progress in biomedical text mining research has primarily focused on entity recognition (locating mentions of species, genes, diseases, clinical findings, etc.) and the extraction of relationships (e.g. between genes/proteins, between diseases and genes etc.). Most of the extracted information is considered as facts and is not placed in the context that delineated the research reporting such facts. In this talk I will overview our efforts to contextualise the results of biomedical text mining by extracting the associated features that charcterise the extracted facts. These include not only negation and speculation, but also associated species, anatomical locations, diseases, aging, etc. I will present several systems and automatically extracted knowledge bases that span themes from biology, bioinformatics and clinical practice.

Speaker Bio:
Dr Goran Nenadic is a Senior Lecturer in the School of Computer Science, University of Manchester, and is a group leader in the Manchester Interdisciplinary BioCenter (MIB). Previously, he was lecturer in the School of Informatics, a post-doctoral research fellow in the same School (former Department of Computation, UMIST), a research fellow at the NLP group, University of Salford, UK, a teaching assistant at the Faculty of Mathematics, University of Belgrade and a visiting teaching assistant in Computational linguistics at the Faculty of Philology, University of Belgrade. Goran has been working in the area of text mining and natural language processing since 1993. His research interests include terminology extraction, acquisition, classification and clustering (mainly in the domain of life sciences), relationship extraction, as well as interoperable architectures for text mining services and digital corpora encoding frameworks. Currently, Goran Nenadic is a principal investigator on a BBSRC project that aims at extraction of associations among various types of entities from the biological literature (bio-MITA - Mining Term Associations from Literature to Support Knowledge Discovery in Biology).