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All the code is available at Sourceforge and GitHub

@Note is published. Please cite using:

  • Anália Lourenço , Rafael Carreira, Sónia Carneiro, Paulo Maia, Daniel Glez-Peña , Florentino Fdez-Riverola , Eugénio C Ferreira , Isabel Rocha and Miguel Rocha.

@Note: A workbench for Biomedical Text Mining. Journal of Biomedical Informatics 2009, 42 710-720


The @Note project has been providing, over the last decade, open-source software libraries and tools addressing the most relevant tasks in the field of biomedical text mining (BTM). These tools have been developed as a collaboration between the Center of Biological Engineering from the University of Minho and the company SilicoLife, with the first version published in 2009.

The current version 2 provides a set of core libraries with a well-defined programming interface (API) addressing the main BTM tasks in both Information Retrieval (IR) and Information Extraction (IE). IR libraries include functions to query specific databases (e.g. Pubmed, patent databases), manage and update query results, download relevant documents, convert PDF to text, assign relevance and corpora management. Regarding IE, the main tasks are Named Entity Recognition (NER), Relationship Extraction (RE) and document clustering, being available several methods for all cases, with both in-house and third-party algorithms, including a machine learning (ML) workbench (BioTML) able to train and apply ML models to user created or existing datasets.

The main project libraries include: core - nuclear data structures and methods; processes - main processes for IR and IE; and machine learning - the framework for ML methods (training and prediction functions). These libraries make use of third-party software libraries in Java, including GATE, Mallet and Carrot. An API is provided allowing the use of the main methods by programmers in their applications, with appropriate examples being provided in the repository.

The project also provides @Note2, an end-user application, which provides user-friendly interfaces for the above listed functionalities, also including the creation of lexical resources (e.g. dictionaries) and a powerful curation environment for NER and RE annotations. The development of the @Note application follows the Model-View-Controller (MVC) paradigm, taking advantage on the plug-in based AI Bench framework (, which provides a clear separation of core libraries and GUI tools, facilitating the development of new features in the form of plug-ins.


SilicoLife Lda.

SilicoLife Lda.- Computational Biology Solutions for the Life Science

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University of Minho

University of Minho



Centre of Biological Engineering

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Copyright 2017
CEB - Centre of Biological Engineering
University of Minho
SilicoLife Lda.

This is free software: you can redistribute it and/or modify
it under the terms of the GNU Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This code is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
GNU Public License for more details.

You should have received a copy of the GNU Public License
along with this code. If not, see

Created inside the BISBII Research Group (
Supported by SilicoLife Lda. (