RT Journal Article
T1 Computational methods for Gene Regulatory Networks reconstruction and analysis: A review
A1 Delgado, Fernando M.
A1 Gómez-Vela, Francisco Antonio
K1 Gene Network
K1 Systems biology
K1 Networks validation
K1 Gene Regulatory Network
K1 Gene Network inference
AB In the recent years, the vast amount of genetic information generated by new-generation approaches, have led to the need of new data handling methods. The integrative analysis of diverse-nature gene information could provide a much-sought overview to study complex biological systems and processes. In this sense, Gene Regulatory Networks (GRN) arise as an increasingly-promising tool for the modelling and analysis of biological processes. This review is an attempt to summarize the state of the art in the field of GRNs. Essential points in the f ield are addressed, thereof: (a) the type of data used for network generation, (b) machine learning methods and tools used for network generation, (c) model optimization and (d) computational approaches used for network validation. This survey is intended to provide an overview of the subject for readers to improve their knowledge in the field of GRN for future research.
PB Elsevier
YR 2018
FD 2018-10-23
LK https://hdl.handle.net/10433/20472
UL https://hdl.handle.net/10433/20472
LA en
NO Artificial Intelligence in Medicine Volume 95, April 2019, Pages 133-145
NO Proyectos de investigaciónIntelligent Data Analysis– TIC200
NO Universidad Pablo de Olavide de Sevilla
DS RIO
RD May 9, 2026