RT Journal Article
T1 Overlapping Community Detection on a Graph of Chemicals, Diseases and Genes for Drug Repositioning and Adverse Reactions Prediction
A1 García-Ochagavía, María Elena
A1 Almeida-Cruz, Yudivián
A1 Estévez-Velarde, Suilán
A1 Alonso-Reina, Aimée
A1 Ochagavía-Roque, María Elena
K1 Drug repositioning
K1 Adverse reactions
K1 Overlapping community detection
K1 Biological network
AB Developing a drug from scratch is a very long and expensive process that has a small probability of success. For this reason, pharmaceutical companies are devoting their efforts to find drugs that could be repositioned. When using a drug to treat a disease is necessary to consider what adverse reactions it may cause, this is why the prediction of adverse reactions is highly related to drug repositioning. We propose the detection of overlapping communities over a biological network of chemicals, diseases and genes in order to find drug-disease pairs that could be used as basis for later drug repositioning and adverse reactions prediction analysis. Of the evaluated overlapping community detection algorithms, OSLOM got the best results, producing 724 communities from which was possible to extract 215944 drug-disease pairs not present in the analyzed graph. We illustrate the usefulness of this set through examples of associations between pairs found in the scientific literature.
PB Universidad Pablo de Olavide
SN 2255-5684
YR 2019
FD 2019-05-03
LK http://hdl.handle.net/10433/10343
UL http://hdl.handle.net/10433/10343
LA en
NO GECONTEC: revista Internacional de Gestión del Conocimiento y la Tecnología, ISSN-e 2255-5684, Vol. 7, Nº. 2, 2019, págs. 80-96
NO URL del artículo en la web de la Revista: https://www.upo.es/revistas/index.php/gecontec/article/view/4081
NO Universidad Pablo de Olavide
DS RIO
RD May 8, 2026