Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research. Bravo, À., Piñero, J., Queralt-Rosinach, N., Rautschka, M., & Furlong, L. I BMC Bioinformatics, 16(1):55, February, 2015. ![Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases.
@article{bravo_extraction_2015,
title = {Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research},
volume = {16},
url = {http://www.biomedcentral.com/1471-2105/16/55},
doi = {10.1186/s12859-015-0472-9},
abstract = {Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases.},
language = {English},
number = {1},
journal = {BMC Bioinformatics},
author = {Bravo, Àlex and Piñero, Janet and Queralt-Rosinach, Núria and Rautschka, Michael and Furlong, Laura I},
month = feb,
year = {2015},
pages = {55},
}
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