GeRNet: A Gene Regulatory Network Tool

DUSSAUT, J.S.; GALLO, C.A.; CRAVERO, F.; MARTÍNEZ, M.J.; CARBALLIDO, J.A.; PONZONI, I.

BIOSYSTEMS

ELSEVIER SCI LTD

Año: 2017

0303-2647

Gene regulatory networks (GRNs) are crucial in every process of lifesince they govern the majority of the molecular processes. Therefore, the taskof assembling these networks is highly important. In particular, the so calledmodel-free approaches have an advantage modeling the complexities ofdynamic molecular networks, since most of the gene networks are hard to bemapped with accuracy by any other mathematical model. A highly abstractmodel-free approach, called rule-based approach, offers several advantagesperforming data-driven analysis; such as the requirement of the least amount ofdata. They also have an important ability to perform inferences: its simplicityallows the inference of large size models with a higher speed of analysis.However, regarding these techniques, the reconstruction of the relationalstructure of the network is partial, hence incomplete, for an effective biologicalanalysis. This situation motivated us to explore the possibility of hybridizingwith other approaches, such as biclustering techniques. This led to incorporate abiclustering tool that finds new relations between the nodes of the GRN. In thiswork we present a new software, called GeRNeT that integrates the algorithmsof GRNCOP2 and BiHEA along a set of tools for interactive visualization,statistical analysis and ontological enrichment of the resulting GRNs. In thisregard, results associated with Alzheimer disease datasets are presented thatshow the usefulness of integrating both bioinformatics tools.