GeRNet: A Gene Regulatory Network Tool

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

BIOSYSTEMS

ELSEVIER SCI LTD

Año: 2017 vol. 162 p. 1 - 11

0303-2647

Gene regulatory networks (GRNs) are crucial in every process of life since they govern the majority of the molecular processes. Therefore, the task of assembling these networks is highly important. In particular, the so called model-free approaches have an advantage modeling the complexities of dy-namic molecular networks, since most of the gene networks are hard to be mapped with accuracy by any other mathematical model. A highly abstract model-free approach, called rule-based approach, offers several advantages performing data-driven analysis; such as the requirement of the least amount of data. They also have an important ability to perform inferences: its sim-plicity allows the inference of large size models with a higher speed of anal-ysis. However, regarding these techniques, the reconstruction of the relation-al structure of the network is partial, hence incomplete, for an effective bio-logical analysis. This situation motivated us to explore the possibility of hy-bridizing with other approaches, such as biclustering techniques. This led to incorporate a biclustering tool that finds new relations between the nodes of the GRN. In this work we present a new software, called GeRNeT that inte-grates the algorithms of GRNCOP2 and BiHEA along a set of tools for inter-active visualization, statistical analysis and ontological enrichment of the re-sulting GRNs. In this regard, results associated with Alzheimer disease da-tasets are presented that show the usefulness of integrating both bioinformat-ics tools.