RT Conference Proceedings
T1 Breast Cancer Biomarker Analysis Using Gene Co-expression Networks
A1 López Fernández, Aurelio
A1 Gallejones Eskubi, Janire
A1 Del Saz Navarro, Dulcenombre de María
A1 Gómez-Vela, Francisco Antonio
K1 Gene expression analysis
K1 Gene co-expression networks
K1 Artificial Intelligence
K1 Bioinformatics
AB Gene co-expression networks have emerged as a robust tool for conducting comprehensive analyses of gene expression patterns. These networks, constructed through inference algorithms, facilitate the exploration of various biological processes and enable the identification of novel biomarkers from which to explore new lines of disease research. This work found that breast cancer stromal cells are strongly dysregulated in genes related to modifications in cellular structures that hold stromal tissue cells together, inflammatory responses, and molecules implicated in immune system regulation. Finally, ANAPC11, LRFN5, COL8A2, TEX11, DOCK9, CPLX1, LONP2, and LAT2 biomarkers were suggested in the context of stromal breast tumors.
PB Springer
YR 2024
FD 2024-08-28
LK https://hdl.handle.net/10433/25202
UL https://hdl.handle.net/10433/25202
LA en
NO López-Fernández, A., Gallejones-Eskubi, J., M. Saz-Navarro, D., A. Gómez-Vela, F. (2024). Breast Cancer Biomarker Analysis Using Gene Co-expression Networks. In: Rojas, I., Ortuño, F., Rojas, F., Herrera, L.J., Valenzuela, O. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2024. Lecture Notes in Computer Science(), vol 14849. Springer, Cham. https://doi.org/10.1007/978-3-031-64636-2_9
NO Departamento de Deporte e Informática, Área de Lenguajes y Sistemas Informáticos
DS RIO
RD Apr 23, 2026