Text Mining Resources for the Life Sciences

Piotr Przybyla, Matthew Shardlow, Sophie Aubin, Robert Bossy, Richard Eckart de Castilho, Stelios Piperidis, John McNaught, Sophia Ananiadou

Research output: Contribution to journalArticlepeer-review


Text mining is a powerful technology for quickly distilling key information from vast quantities of biomedical literature. However, to harness this power the researcher must be well versed in the availability, suitability, adaptability, interoperability and comparative accuracy of current text mining resources. In this survey, we give an overview of the text mining resources that exist in the life sciences to help researchers, especially those employed in biocuration, to engage with text mining in their own work. We categorise the various resources under three sections: Content Discovery looks at where and how to find biomedical publications for text mining; Knowledge Encoding describes the formats used to represent the different levels of information associated with content that enable text mining, including those formats used to carry such information between processes; Tools and Services gives an overview of workflow management systems that can be used to rapidly configure and compare domain- and task-speicfic processes, via access to a wide range of pre-built tools. We also provide links to relevant repositories in each section to enable the reader to find resources relevant to their own area of interest. Throughout this work we give a special focus to resources that are interoperable — those that have the crucial ability to share information, enabling smooth integration and reusability.
Original languageEnglish
Number of pages30
Early online date21 Nov 2016
Publication statusPublished - 2016


  • text mining
  • biocuration
  • interoperability
  • text mining resources
  • annotation formats
  • content discovery
  • knowledge encoding
  • repositories
  • aggregators

Research Beacons, Institutes and Platforms

  • Manchester Institute of Biotechnology


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