Data management and analysis for risk assessment of rare and complex diseases such as Neuroblastoma require efficient management of multidisciplinary data. Recent advances in genomic testing are revealing new publicly available data whose storage and analysis with clinical and genomic data is becoming a big challenge. The use of Conceptual Modeling (CM) techniques helps to define and structure the Neuroblastoma domain, which serves as a basis to determine the information required for diagnosing

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... the disease. It is important to highlight that a Genomic Information System (GeIS) based on a conceptual model allows improving the adaptation of new requirements of the domain, and greatly simplifies the integration and management of heterogeneous and homogeneous data. The main objectives of this work are: i) to present a Conceptual Model of Neuroblastoma (CMN), which defines all elements involved in the clinical and genomic domain. ii) to apply the SILE method, in order to obtain all (clinically) relevant variations associated with Neuroblastoma from genomic data sources. The developed GeIS is intended to make the correct exploitation of the validated data set to provide an early and efficient risk assessment for patients with Neuroblastoma.