title: From phenotype to genotype in complex brain networks.
abstract: Generative models are a popular instrument for illuminating the relationships between the hidden variables driving the growth of a complex network and its final topological characteristics, a process known as the "genotype to phenotype problem". However, the definition of a complete methodology encompassing all stages of the analysis, and in particular the validation of the final model, is still an open problem. We here discuss a framework that allows to quantitatively optimise and validate each step of the model creation process. It is based on the execution of a classification task, and on estimating the additional precision provided by the modelled genotype. This encompasses the three main steps of the model creation, namely the selection of topological features, the optimisation of the parameters of the generative model, and the validation of the obtained results. We provide a minimum requirement for a generative model to be useful, prescribing the function mapping genotype to phenotype to be non-monotonic; and we further show how a previously published model does not fulfil such condition, casting doubts on its fitness for the study of neurological disorders. The generality of such framework guarantees its applicability beyond neuroscience, like the emergence of social or technological networks.
authors.affiliation: Science and Technology Faculty, Computer Science Department, Universidade Nova de Lisboa, Lisboa, Portugal.|Innaxis Foundation &Research Institute, José Ortega y Gasset 20, 28006, Madrid, Spain.
authors.forename: Massimiliano
authors.initials: M
authors.lastname: Zanin
authors.affiliation: Science and Technology Faculty, Computer Science Department, Universidade Nova de Lisboa, Lisboa, Portugal.
authors.forename: Marco
authors.initials: M
authors.lastname: Correia
authors.affiliation: Departamento de Engenharia Electrotécnica, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Lisboa, Portugal.
authors.forename: Pedro A C
authors.initials: PA
authors.lastname: Sousa
authors.affiliation: Science and Technology Faculty, Computer Science Department, Universidade Nova de Lisboa, Lisboa, Portugal.
authors.forename: Jorge
authors.initials: J
authors.lastname: Cruz
mesh_terms: D000544:Alzheimer Disease / Q000235:genetics / Q000473:pathology; D001921:Brain / Q000473:pathology*; D005838:Genotype; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000473:pathology*; D010641:Phenotype; D011336:Probability; D015203:Reproducibility of Results