Abstract
The accumulated experiments show that lncRNA has a role in biophysiological and case processes. Prediction of the relationship between diseases and lncRNA will contribute to clarify the etiology of diseases, develop new drugs and treat complex diseases. However, the traditional biological experiment method has long experiment period and high cost. Therefore, based on existing biological data and biological experimental data, data mining techniques have been used to propose many models and methods to predict the lncRNA-disease correlation. This article will provide a specific introduction to lncRNA and disease-related databases, which summarizes some relevant predictions classical models (matrix factorization, heterogeneous networks, machine learning). At the end of the article, the problems of lncRNA and the current prediction of the disease are analyzed, and some ideas and help are provided for later researchers.
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