Dr Martin Gerner

Dr Martin Gerner

PhD student (now with Avego)


  • Named-entity recognition and term mining

    Recognizing terms and named entities in research articles and mapping them to unique identifiers is an important first step in most text mining software. This is a challenging task because of ambiguity and variation in how entities and concepts are named and used in particular in the biological literature. Our…

  • Mining term associations and events from bio-literature

    This is a long-term project that aims at developing text mining methods that can provide efficient and sophisticated knowledge acquisition, offer plausible hypotheses for testing, prevent unnecessary repetition of previous work, and help in experimental design for specific research scenarios. We investigate various text mining approaches to establishing literature-based associations…

  • Integration of text and data mining in life sciences

    There have been numerous efforts to provide tools for storing, extracting and analysing data in life sciences. Interoperability and integration of such efforts is a challenging issue, not only technically (e.g. different formats, protocols, encodings) but also more importantly semantically. We are involved in a number of community-driven initiatives to…