miRNA-Disease Associations Prediction Based on Neural Tensor Decomposition
| Autor: | Jiawei Luo, Hao Wu, Yi Liu |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Intelligent Computing Theories and Application ISBN: 9783030845315 ICIC (3) |
| Popis: | As a kind of regulatory factor in the human body, miRNAs function by targeting mRNAs. Dysfunction of miRNAs has an important relationship with diseases. miRNA-disease associations prediction algorithm aims to find potential pathogenic miRNAs based on known miRNA-related and disease-related data. With the development of miRNA-disease prediction algorithm research and the accumulation of biological data, integrating gene information in the prediction of pathogenic miRNAs is not only helpful to improve the accuracy of prediction but also helpful to further explore the pathogenesis of diseases. Therefore, in this paper, we propose a miRNA-disease association prediction algorithm, which is based on neural tensor decomposition, named NTDMDA, integrating the idea of weighted K nearest neighbors (WKNN) and a neural tensor decomposition model to identify pathogenic miRNAs. The experimental results show that the performance of NTDMDA is better than other comparison methods (improving up to at least 1.4% in AUC) in the prediction of miRNA-disease associations. At the same time, NTDMDA can realize the prediction of miRNA-gene-disease associations and provide richer information for the understanding of the complex biological mechanism between miRNAs and diseases. |
| Databáze: | OpenAIRE |
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