The analysis of genomic data has been used to generate information about genetic variants and expression patterns correlated with specific physical traits. In the last decades, these analyses have evolved toward analyzing thousands of entities at the same time. Moreover, these analyses have produced an enormous amount of biomedical literature reporting associations between genes and diseases. In this scenario, pattern recognition techniques have been truly useful, so a review of how these techniques have been applied is relevant. Thus, in this chapter we present a brief introduction to the high-throughput sequencing methodologies. Then, we describe the process of identification of genomic variants and genetic expression profiles that have been used for the diagnostic of diseases, followed by a general overview of the gene-disease association extraction from biomedical literature.
CITATION STYLE
Jiménez-Jacinto, V., Gómez-Romero, L., & Méndez-Cruz, C. F. (2020). Pattern Recognition Applied to the Analysis of Genomic Data and Its Association to Diseases. In STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics and Health (pp. 35–61). Springer Nature. https://doi.org/10.1007/978-3-030-38021-2_2
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