A Comprehensive Approach for the Conceptual Modeling of Genomic Data

The human genome is traditionally represented as a DNA sequence of three billion base pairs. However, its intricacies are captured by many more complex signals, representing DNA variations, the expression of gene activity, or DNA's structural rearrangements; a rich set of data formats is used to represent such signals. Different conceptual models explain such elaborate structure and behavior. Among them, the Conceptual Schema of the Human Genome (CSG) provides a concept-oriented, top-down representation of the genome behavior - independent of data formats. The Genomic Conceptual Model (GCM) instead provides a data-oriented, bottom-up representation, targeting a well-organized, unified description of these formats. We hereby propose to join these two approaches to achieve a more complete vision, linking (1) a concepts layer, describing genome elements and their conceptual connections, with (2) a data layer, describing datasets derived from genome sequencing with specific technologies. The link is established when specific genomic data types are chosen in the data layer, thereby triggering the selection of a view in the concepts layer. The benefit is mutual, as data records can be semantically described by high-level concepts and exploit their links. In turn, the continuously evolving abstract model can be extended thanks to the input provided by real datasets. As a result, it will be possible to express queries that employ a holistic conceptual perspective on the genome, directly translated onto data-oriented terms and organization. The approach is here exemplified using the DNA variation data type but is applicable to all genomic information.