A "big data oriented" and "complex network based" model supporting the uniform investigation of heterogeneous personalized medicine data

In the big data era, the number, the volume and the variety of available data sources are dramatically increasing. This becomes a great issue to address in all the research fields. Personalized medicine does not escape this trend. However, as generally happens, what is a problem, if solved, can become an opportunity. As a consequence, if we were able to define a model to represent and handle data coming from disparate contexts of medicine, we could use it to face different problems in this scenario. A concept and/or an approach designed to solve an open problem in one of these contexts could be transposed to address open issues in several other ones. In this paper, we propose a "big data oriented" and a "complex network based" model and a set of associated parameters, and we apply them to investigate three very different neurological disorders, namely Creutzfeldt-Jacob Disease, Childhood Absence Epilepsy and Alzheimer's Disease.