@Note is Biomedical Text Mining platform that copes with major Information Retrieval and Information Extraction tasks and promotes multi-disciplinary research. In fact, it aims to provide support to three different usage roles: biologists, text miners and application developers. @Note was developed in collaboration with the CCTC (Centro de Ciencias e Tecnologias da Computacion) and the BioPSeg (BioProcess Systems Engineering group) of the University of Minho.

Currently, @Note workbench includes plug-ins for:

  • querying PubMed and retrieving full-texts from open-acess and subscribed journals;
  • managing terminological resources (namely dictionaries and expert-specified entity recognition rules);
  • automatically recognising biological entities based on problem-specific terminological resources;
  • manually curating entity annotations and refining lexical resources.
Detailed information on both @Note workbench and individual plug-ins, namely examples on how to deploy new projects and construct problem-specific resources, as well as download and install instructions can be found at

Visit our repositories on

2017 Sistemas Informáticos de Nueva Generación