Abstract
The advent of Next Generation Sequencing (NGS) technologies and the reduction of sequencing costs, characterized the last decades by a massive production of experimental data. These data cover a wide range of biological experiments derived from several sequencing strategies, producing a big amount of heterogeneous data. They are often linked to a set of related metadata that are essential to describe experiments and the analyzed samples, with also information about patients from which samples have been collected. Nowadays, browsing all these data and retrieving significant insights from them is a big challenge that has been already faced with different techniques in order to facilitate their accessibility and interoperability. In this work, we focus on genomic data of cancer and related metadata exploiting domain-specific ontologies in order to allow executing taxonomy-based relaxed queries. In particular, we apply the upward and downward query extension methods to obtain a finer or coarser granularity of the requested information. We define diverse use cases with which a user can perform a query specifying particular attributes related to metadata or genomic data, even if they are not available in the considered repository. Thus, we are able to extract the requested data through the use of domain-specific ontologies of The Open Biological and Biomedical Ontology (OBO) Foundry. Finally, we propose a new ontological software layer, which allows users to interact with experimental data and metadata without knowledge about their representation schema.
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Cappelli, E., Weitschek, E., Cumbo, F. (2020). Extending Knowledge on Genomic Data and Metadata of Cancer by Exploiting Taxonomy-Based Relaxed Queries on Domain-Specific Ontologies. In: Cazzaniga, P., Besozzi, D., Merelli, I., Manzoni, L. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2019. Lecture Notes in Computer Science(), vol 12313. Springer, Cham. https://doi.org/10.1007/978-3-030-63061-4_4
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DOI: https://doi.org/10.1007/978-3-030-63061-4_4
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