Inference of Gene Regulatory Networks based on Association Rules

GALLO CRISTIAN; CARBALLIDO JESSICA ANDREA; PONZONI IGNACIO

Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data

Wiley

Año: 2014; p. 1 - 38

The most important and widespread mechanism used by cells to regulate molecular functions or biological process is the coordinate transcriptional and post-transcriptional network of the interacting genes or their products. In this way, and under the command of Transcription Factors (TFs), each gene influences the activity of the cell by generating messenger RNA (mRNA) that guides the synthesis of proteins by ribosomes in the cytoplasm. Some of these gene products generated are themselves TFs that return to the nucleus (in eukaryotes) to control the expression of one or several genes. This complicated means of controlling gene expression can be represented as a Gene Regulatory Network (GRN). The GRNs are complex interaction maps that describe putative associations among gene products which orchestrate the living organism functions. The reverse engineering of GRNs is a paradigm with great promise for analyzing and constructing biological networks [Kitano, 2000; Cho et al., 2007; Csete and Doyle, 2002]; it is an effective way of utilizing experimental data to determine the underlying network of a given model, and constitutes an open research problem in bioinformatics.