title: Studying the complex expression dependences between sets of coexpressed genes.
abstract: Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.
authors.affiliation: Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.
authors.forename: Mario
authors.initials: M
authors.lastname: Huerta
authors.affiliation: Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.
authors.forename: Oriol
authors.identifier: 0000-0002-7581-3220
authors.initials: O
authors.lastname: Casanova
authors.affiliation: Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.
authors.forename: Roberto
authors.initials: R
authors.lastname: Barchino
authors.affiliation: Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.
authors.forename: Jose
authors.identifier: 0000-0001-9869-8897
authors.initials: J
authors.lastname: Flores
authors.affiliation: Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.
authors.forename: Enrique
authors.initials: E
authors.lastname: Querol
authors.affiliation: Laboratorio de Inmunología, CENUR del Noroeste, Universidad de la República-Salto, Rivera 1350, 50000 Salto, Uruguay.
authors.forename: Juan
authors.identifier: 0000-0003-1380-8036
authors.initials: J
authors.lastname: Cedano
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D030541:Databases, Genetic; D015870:Gene Expression / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans