Publications

Our team has a strong track record in text and data mining to power molecular and competitor intelligence in drug discovery. Here are some of the most relevant ones:

  • Drug discovery FAQs: workflows for answering multidomain drug discovery questions Drug Discovery Today (2014) doi:10.1016/j.drudis.2014.11.006
  • Visualizing the drug target landscape Drug Discovery Today (2010) 15, 3-15 doi:10.1016/j.drudis.2009.09.011
  • API-centric Linked Data Integration Web Semantics: Science, Services and Agents on the World Wide Web (2014)  doi:10.1016/j.drudis.2009.09.011
  • Reuniting data and narrative in scientific articles Insights: the UKSG journal Link
  • Scientific competency questions as the basis for semantically enriched open pharmacological space development Drug Discovery Today Volume 18 (2013) doi:10.1016/j.drudis.2013.05.008
  • Precompetitive activity to address the biological data needs of drug discovery Nature Reviews Drug Discovery 2014 Link
  • Open PHACTS: semantic interoperability for drug discovery  Drug Discov Today (2012) doi:10.1016/j.drudis.2012.05.016
  • Applying Linked Data Approaches to Pharmacology: Architectural Decisions and Implementation Semantic Web Journal (2013) Link
  • Towards interoperable bioscience data Nature Genet. (2012) 44 121-6 doi: 10.1038/ng.1054
  • Systems chemical biology and the Semantic Web: what they mean for the future of drug discovery research Drug Discovery Today (2012)  doi:10.1016/j.drudis.2011.12.019
  • Empowering Industrial Research With Shared Biomedical Vocabularies Drug Discovery Today (2011) 16 940-947 doi:10.1016/j.drudis.2011.09.013 
  • Minimum information about a bioactive entity (MIABE) Nature Reviews Drug Discovery (2011) 10661-669 doi:10.1038/nrd3503
  • Lowering industry firewalls: pre-competitive informatics initiatives in drug discoveryNature Reviews Drug Discovery (2009) 8, 701-708 doi:10.1038/nrd2944
  • Drug Target Central Expert Opinion on Drug Discovery (2009) 8, 857-872 doi:10.1517/17460440903049290
  • High-throughput electronic biology: mining information for drug discovery Nature Reviews Drug Discovery (2007), 220Ð230 doi:10.1038/nrd2265
  • System and method for the computer-assisted identification of drugs and indications US2005060305 (2005) Link