Abstract
The identification of relevant genomic variants is key for providing a more reliable and precise diagnosis of diseases with a known genetic component. Nevertheless, this is a complex and time-consuming process that is affected by multiple factors such as the quality of the information and the heterogeneity of the data sources. Another characteristic of genomic knowledge is its evolution, which may cause the number of known relevant variants to change over time. This forces the experts to repeat the process multiple times to keep the information and the affected diagnosis correctly updated. For a particular disease, new relevant variants can be identified, while old ones may not be as significant as initially considered. The SILE method aims to systematize and facilitate the variant identification process, reducing the time required for the analysis and allowing the experts to repeat it as many times as needed in order to keep up to date with new knowledge. To highlight the importance of the temporal dimension and the need for such methods, SILE has been applied to a case study at two different time points to compare how the number of variants initially considered to be relevant has evolved during a short period of time. The results obtained demonstrate the need for considering the temporal dimension in the development of methods such as SILE in order to provide a more accurate and up-to-date genetic diagnosis.
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Acknowledgements
This work has been developed with the financial support of the Spanish State Research Agency and the Generalidad Valenciana under the projects TIN2016-80811-P and PROMETEO/2018/176, co-financed with ERDF.
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Costa, M., León, A., Pastor, Ó. (2020). The Importance of the Temporal Dimension in Identifying Relevant Genomic Variants: A Case Study. In: Grossmann, G., Ram, S. (eds) Advances in Conceptual Modeling. ER 2020. Lecture Notes in Computer Science(), vol 12584. Springer, Cham. https://doi.org/10.1007/978-3-030-65847-2_5
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