title: Computational models reconstruct gene regulatory networks.
abstract: The post-genomic era is flooded with data from high-throughput techniques such as cDNA microarrays. In the field of systems biology the reconstruction of gene regulatory networks from gene expression data is one of the major problems in understanding complex cell functions. Drawing conclusions from microarray data requires sophisticated computational analyses that will explore causal genetic relations. In this paper we provide a brief summary of some of the most recent and promising computational models and mathematical frameworks used to reconstruct, model and infer gene regulatory networks from data.
authors.affiliation: Medical Physics Department, University of Patras, Rio, 22500, Greece.
authors.forename: Anastasios
authors.initials: A
authors.lastname: Bezerianos
authors.forename: Ioannis A
authors.initials: IA
authors.lastname: Maraziotis
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D011336:Probability