Event-based text mining for biology and functional genomics

Sophia Ananiadou, Paul Thompson, Raheel Nawaz, John McNaught, Douglas Kell

Research output: Contribution to journalArticlepeer-review


The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research.
Original languageEnglish
Pages (from-to)213-30
Number of pages17
JournalBriefings in functional genomics
Issue number3
Early online date6 Jun 2014
Publication statusPublished - May 2015


  • text mining
  • event extraction
  • semantic annotation
  • semantic search


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