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Identification of human microRNA-disease association via low-rank approximation-based link propagation and multiple kernel learning

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Abstract

Numerous studies have demonstrated that human microRNAs (miRNAs) and diseases are associated and studies on the microRNA-disease association (MDA) have been conducted. We developed a model using a low-rank approximation-based link propagation algorithm with Hilbert–Schmidt independence criterion-based multiple kernel learning (HSIC-MKL) to solve the problem of the large time commitment and cost of traditional biological experiments involving miRNAs and diseases, and improve the model effect. We constructed three kernels in miRNA and disease space and conducted kernel fusion using HSIC-MKL. Link propagation uses matrix factorization and matrix approximation to effectively reduce computation and time costs. The results of the experiment show that the approach we proposed has a good effect, and, in some respects, exceeds what existing models can do.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 62072385, 62172076, and U22A2038), the Municipal Government of Quzhou (2022D040), and the Zhejiang Provincial Natural Science Foundation of China (No. LY23F020003).

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  1. These authors contributed equally to this work.

Authors and Affiliations

  1. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Yizheng Wang & Quan Zou

  2. Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, 324000, China

    Yizheng Wang, Quan Zou & Yijie Ding

  3. Beidahuang Industry Group General Hospital, Harbin, 150088, China

    Xin Zhang

  4. School of Informatics, Xiamen University, Xiamen, 361005, China

    Ying Ju

  5. Department of Anesthesiology, Hospital (T.C.M) Affiliated to Southwest Medical University, Luzhou, 646000, China

    Qing Liu & Ying Zhang

  6. Software Engineering College, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    Yazhou Zhang

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  1. Yizheng Wang
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  2. Xin Zhang
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  4. Qing Liu
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  8. Ying Zhang
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Corresponding authors

Correspondence to Yijie Ding or Ying Zhang.

Additional information

Yizheng Wang is a postgraduate in the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, China. He received the Bachelor of Engineering degree in computer science and technology from Yanshan University, China in 2022. His research interests include bioinformatics and machine learning.

Xin Zhang is a deputy chief physician of Beidahuang Industry Group General Hospital, China. He graduated from Harbin Medical University, China in 2006, and his research direction is basic medicine and lung cancer.

Ying Ju received her PhD degree in Biomedical Engineering from Xi’an Jiaotong University, China. She is an associate professor with the Department of Computer Science, Xiamen University, China. She has published more than 15 papers in journal and conference. Her main research interest is biomedical engineering.

Qing Liu is a chief physician of Department of Anesthesiology, Hospital (T.C.M) Affiliated to Southwest Medical University, China. He received his master’s degree in Medicine in 2004, and his research interest is mechanism of neuropathic pain.

Quan Zou received the BSc, MSc, and the PhD degrees in computer science from Harbin Institute of Technology, China in 2004, 2007 and 2009, respectively. He is currently a professor in the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China. His research is in the areas of bioinformatics, machine learning and parallel computing. Several related works have been published by Science, Briefings in Bioinformatics, Bioinformatics, etc. Google scholar showed that his more than 100 papers have been cited more than 16000 times. He is the editor-in-chief of Current Bioinformatics and Computers in Biology and Medicine. He was selected as one of the Clarivate Analytics Highly Cited Researchers in 2018–2022.

Yazhou Zhang received PhD degree in computer applications technology from Tianjin University, China in 2020. He has published more than 35 papers, including CCF ranking A/B conference papers (e.g., IJCAI, EMNLP, CIKM, NAACL) and top journal papers (e.g., IEEE Trans. on Fuzzy System, Information Fusion, ACM Trans. on Internet Technology, Theoretical Computer Science, Neural Networks).

Yijie Ding received the PhD degree in computer science from the School of Computer Science and Technology, Tianjin University, China in 2018. He is currently an Associate Professor with the Yangtze Delta Region Institute, University of Electronic Science and Technology of China, China. His research interests include bioinformatics and machine learning. Several related works have been published by Briefings in Bioinformatics, IEEE TFS, IEEE TAI, IEEE/ACM TCBB, IEEE JBHI, Information Sciences, Knowledge-Based Systems, Applied Soft Computing, and Neurocomputing.

Ying Zhang is a chief physician of Department of Anesthesiology, Hospital (T.C.M) Affiliated to Southwest Medical University, China. She is studying for her PhD at Macau University of Science and Technology, China. She received her master’s degree in Medicine in 2011, and her research interest is mechanism of neuropathic pain and protective mechanism of postoperative cognitive function.

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Identification of human microRNA-disease association via low-rank approximation-based link propagation and multiple kernel learning

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Wang, Y., Zhang, X., Ju, Y. et al. Identification of human microRNA-disease association via low-rank approximation-based link propagation and multiple kernel learning. Front. Comput. Sci. 18, 182903 (2024). https://doi.org/10.1007/s11704-023-2490-5

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