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RWSF-BLP: a novel lncRNA-disease association prediction model using random walk-based multi-similarity fusion and bidirectional label propagation

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Abstract

An increasing number of studies and experiments have demonstrated that long noncoding RNAs (lncRNAs) have a massive impact on various biological processes. Predicting potential associations between lncRNAs and diseases not only can improve our understanding of the molecular mechanisms of human diseases but also can facilitate the identification of biomarkers for disease diagnosis, treatment, and prevention. However, identifying such associations through experiments is costly and demanding, thereby prompting researchers to develop computational methods to complement these experiments. In this paper, we constructed a novel model called RWSF-BLP (a novel lncRNA-disease association prediction model using Random Walk-based multi-Similarity Fusion and Bidirectional Label Propagation), which applies an efficient random walk-based multi-similarity fusion (RWSF) method to fuse different similarity matrices and utilizes bidirectional label propagation to predict potential lncRNA-disease associations. Leave-one-out cross-validation (LOOCV) and 5-fold cross-validation (5-fold-CV) were implemented in the evaluation RWSF-BLP performance. Results showed that, RWSF-BLP has reliable AUCs of 0.9086 and 0.9115 ± 0.0044 under the framework of LOOCV and 5-fold-CV and outperformed other four canonical methods. Case studies on lung cancer and leukemia demonstrated that potential lncRNA-disease associations can be predicted through our method. Therefore, our method can accurately infer potential lncRNA-disease associations and may be a good choice in future biomedical research.

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Funding

This work was supported by the National Natural Science Foundation of China (62002070, 618002072), the Natural Science Foundation of Guangdong Province (2018A030313389), the Science and Technology Plan Project of Guangdong Province (2019B010139002, 2018B030323026, 2017A040405050, 2016B030306004), and the Science and Technology Program of Guangzhou (201902020006, 201902020012, 201907010021).Yuping Sun is the corresponding author.

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  1. School of Computer Science, Guangdong University of Technology, Guangzhou, China

    Guobo Xie, Bin Huang, Yuping Sun, Changhai Wu & Yuqiong Han

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  1. Guobo Xie
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  2. Bin Huang
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  3. Yuping Sun
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  4. Changhai Wu
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Correspondence to Yuping Sun.

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Xie, G., Huang, B., Sun, Y. et al. RWSF-BLP: a novel lncRNA-disease association prediction model using random walk-based multi-similarity fusion and bidirectional label propagation. Mol Genet Genomics 296, 473–483 (2021). https://doi.org/10.1007/s00438-021-01764-3

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