Abstract
Dysregulation of microRNAs (miRNAs) has been implicated in human disease. Further, a panel of vital circulating microRNA has also been involved in human diseases. Therefore, prediction of human disease using liquid biopsy of miRNAs would be useful in human healthcare. However, to do so, it is crucial to infer miRNAs associated with disease-related target proteins. Prediction computing of miRNA and disease has been advanced by miRNA-miRNA similarity, miRNA-messenger RNA (mRNA) interaction, disease-disease similarity, Gaussian kernel similarity, and machine learning. But these data science-based mathematical algorithms have not shown the etiology of miRNA-associated diseases. In addition, data science analysis was plagued by statistically inevitable computational errors and biases.
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Fujii, Y.R. (2023). Vital METS/MIRAI. In: The MicroRNA Quantum Code Book. Springer, Singapore. https://doi.org/10.1007/978-981-19-8586-7_5
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