A Study on a Deep Learning Model for Predicting MicroRNA-Gene Association Using Distance-Based Labeling Methods 


Vol. 47,  No. 10, pp. 1637-1644, Oct.  2022
10.7840/kics.2022.47.10.1637


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  Abstract

MicroRNAs (miRNAs) are important RNAs that regulate gene expression. Finding associations between microRNAs and genes can help us understand how microRNAs that are so small and difficult to experiment, and are also effective in diagnosing a patient's disease. In this paper, we present a long-short term memory (LSTM) based deep learning model that predicts the association of microRNAs and genes together with a new labeling method based on distance measurement of miRNA-gene pairs. The verification test results are presented. The ROC curve of the deep learning model presented in this study achieved a maximum of 0.95.

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[IEEE Style]

J. Kim, S. Yoon, I. Hwang, K. Lee, "A Study on a Deep Learning Model for Predicting MicroRNA-Gene Association Using Distance-Based Labeling Methods," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 10, pp. 1637-1644, 2022. DOI: 10.7840/kics.2022.47.10.1637.

[ACM Style]

Jaein Kim, Seung-Won Yoon, In-Woo Hwang, and Kyu-Chul Lee. 2022. A Study on a Deep Learning Model for Predicting MicroRNA-Gene Association Using Distance-Based Labeling Methods. The Journal of Korean Institute of Communications and Information Sciences, 47, 10, (2022), 1637-1644. DOI: 10.7840/kics.2022.47.10.1637.

[KICS Style]

Jaein Kim, Seung-Won Yoon, In-Woo Hwang, Kyu-Chul Lee, "A Study on a Deep Learning Model for Predicting MicroRNA-Gene Association Using Distance-Based Labeling Methods," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 10, pp. 1637-1644, 10. 2022. (https://doi.org/10.7840/kics.2022.47.10.1637)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880