Identifying Drug Repositioning Targets using Text Mining

Eduardo Barçante, Milene Jezuz, Felipe Duval, Ernesto Caffarena, Oswaldo G. Cruz, Fabricio Silva

2014

Abstract

The current scenario of computational biology relies on the know-how of many technological areas, with focus on information, computing, and, particularly on the construction and use of existing Internet databases such as MEDLINE, PubMed and PDB. In recent years, these databases provide an environment to access, integrate and produce new knowledge by storing ever increasing volumes of genetic or protein data. The transformation and management of these data in a different way than from the one that were originally thought can be a challenge for research in biology. The problems appear by the lack of textual structure or appropriate markup tags. The main goal of this work is to explore the PubMed database, the main source of information about health sciences, from the National Library of Medicine. By means of this database of digital textual documents, we aim to develop a method capable of identifying protein terms that will serve as a substrate to laboratory practices for repositioning drugs. In this perspective, in this work we use text mining to extract terms related to protein names in the field of neglected diseases.

Paper Citation

in Harvard Style

Barçante E., Jezuz M., Duval F., Caffarena E., G. Cruz O. and Silva F. (2014). Identifying Drug Repositioning Targets using Text Mining . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 348-353. DOI: 10.5220/0005134903480353

in Bibtex Style

@conference{kdir14,
author={Eduardo Barçante and Milene Jezuz and Felipe Duval and Ernesto Caffarena and Oswaldo G. Cruz and Fabricio Silva},
title={Identifying Drug Repositioning Targets using Text Mining},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={348-353},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005134903480353},
isbn={978-989-758-048-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - Identifying Drug Repositioning Targets using Text Mining
SN - 978-989-758-048-2
AU - Barçante E.
AU - Jezuz M.
AU - Duval F.
AU - Caffarena E.
AU - G. Cruz O.
AU - Silva F.
PY - 2014
SP - 348
EP - 353
DO - 10.5220/0005134903480353